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Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model (Released in the STEO March 1998)  

Reports and Publications (EIA)

The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.

1998-01-01T23:59:59.000Z

2

AN APPLICATION OF URBANSIM TO THE AUSTIN, TEXAS REGION: INTEGRATED-MODEL FORECASTS FOR THE YEAR 2030  

E-Print Network [OSTI]

AN APPLICATION OF URBANSIM TO THE AUSTIN, TEXAS REGION: INTEGRATED-MODEL FORECASTS FOR THE YEAR, as well as energy consumption and greenhouse gas emissions. This work describes the modeling of year-2030 policies significantly impact the region's future land use patterns, traffic conditions, greenhouse gas

Kockelman, Kara M.

3

Depositional sequences and integrated recovery efficiency forecast models for San Andres and Clearfork Units in the Central Basin Platform and the Northern Shelf, west Texas  

E-Print Network [OSTI]

This paper develops depositional sequences of the carbonate ramp and the carbonate shelf models for an idealized cycle and multiple cycles of depositions. Based on the developed depositional sequences, the integrated recovery efficiency forecast...

Shao, Hongbin

2012-06-07T23:59:59.000Z

4

Forecasting 65+ travel : an integration of cohort analysis and travel demand modeling  

E-Print Network [OSTI]

Over the next 30 years, the Boomers will double the 65+ population in the United States and comprise a new generation of older Americans. This study forecasts the aging Boomers' travel. Previous efforts to forecast 65+ ...

Bush, Sarah, 1973-

2003-01-01T23:59:59.000Z

5

Forecasting wave height probabilities with numerical weather prediction models  

E-Print Network [OSTI]

Forecasting wave height probabilities with numerical weather prediction models Mark S. Roulstona; Numerical weather prediction 1. Introduction Wave forecasting is now an integral part of operational weather methods for generating such forecasts from numerical model output from the European Centre for Medium

Stevenson, Paul

6

Weather Research and Forecasting Model 2.2 Documentation  

E-Print Network [OSTI]

................................................................................................. 20 3.1.2 Integrate's Flow of ControlWeather Research and Forecasting Model 2.2 Documentation: A Step-by-step guide of a Model Run .......................................................................................................................... 19 3.1 The Integrate Subroutine

Sadjadi, S. Masoud

7

Aggregate vehicle travel forecasting model  

SciTech Connect (OSTI)

This report describes a model for forecasting total US highway travel by all vehicle types, and its implementation in the form of a personal computer program. The model comprises a short-run, econometrically-based module for forecasting through the year 2000, as well as a structural, scenario-based longer term module for forecasting through 2030. The short-term module is driven primarily by economic variables. It includes a detailed vehicle stock model and permits the estimation of fuel use as well as vehicle travel. The longer-tenn module depends on demographic factors to a greater extent, but also on trends in key parameters such as vehicle load factors, and the dematerialization of GNP. Both passenger and freight vehicle movements are accounted for in both modules. The model has been implemented as a compiled program in the Fox-Pro database management system operating in the Windows environment.

Greene, D.L.; Chin, Shih-Miao; Gibson, R. [Tennessee Univ., Knoxville, TN (United States)

1995-05-01T23:59:59.000Z

8

Integrating agricultural pest biocontrol into forecasts of energy biomass production  

E-Print Network [OSTI]

Analysis Integrating agricultural pest biocontrol into forecasts of energy biomass production T pollution, greenhouse gas emissions, and soil erosion (Nash, 2007; Searchinger et al., 2008). On the other

Gratton, Claudio

9

Weather forecast-based optimization of integrated energy systems.  

SciTech Connect (OSTI)

In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.

Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

2009-03-01T23:59:59.000Z

10

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect (OSTI)

Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18T23:59:59.000Z

11

New Concepts in Wind Power Forecasting Models  

E-Print Network [OSTI]

New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind for more accurate short term wind power forecasting models has led to solid and impressive development

Kemner, Ken

12

A new improved forecasting method integrated fuzzy time series with the exponential smoothing method  

Science Journals Connector (OSTI)

This paper presents a new method of integrated fuzzy time series with the exponential smoothing method to forecast university enrolments. The data of historical enrolments of the University of Alabama shown in Liu et al. (2011) are adopted to illustrate the forecasting process of the proposed method. A comparison has been made with five previous fuzzy time series models. Meanwhile, the mean squared error has also been calculated as the evaluation criterion to illustrate the performance of the proposed method. The empirical analysis shows that the proposed model reflects the fluctuations in fuzzy time series better and provides better overall forecasting results than the five listed previous models.

Peng Ge; Jun Wang; Peiyu Ren; Huafeng Gao; Yuyan Luo

2013-01-01T23:59:59.000Z

13

Forecasting correlated time series with exponential smoothing models  

Science Journals Connector (OSTI)

This paper presents the Bayesian analysis of a general multivariate exponential smoothing model that allows us to forecast time series jointly, subject to correlated random disturbances. The general multivariate model, which can be formulated as a seemingly unrelated regression model, includes the previously studied homogeneous multivariate Holt-Winters’ model as a special case when all of the univariate series share a common structure. MCMC simulation techniques are required in order to approach the non-analytically tractable posterior distribution of the model parameters. The predictive distribution is then estimated using Monte Carlo integration. A Bayesian model selection criterion is introduced into the forecasting scheme for selecting the most adequate multivariate model for describing the behaviour of the time series under study. The forecasting performance of this procedure is tested using some real examples.

Ana Corberán-Vallet; José D. Bermúdez; Enriqueta Vercher

2011-01-01T23:59:59.000Z

14

Ensemble typhoon quantitative precipitation forecasts model in Taiwan  

Science Journals Connector (OSTI)

In this study, an ensemble typhoon quantitative precipitation forecast (ETQPF) model was developed to provide typhoon rainfall forecasts for Taiwan. The ETQPF rainfall forecast is obtained by averaging the pick-out cases, which are screened at a ...

Jing-Shan Hong; Chin-Tzu Fong; Ling-Feng Hsiao; Yi-Chiang Yu; Chian-You Tzeng

15

Analysis of the energy and environmental effects of green car deployment by an integrating energy system model with a forecasting model  

Science Journals Connector (OSTI)

By 2020, Korea has set itself the challenging target of reducing nationwide greenhouse gas emissions by 30%, more than the BAU (Business as Usual) scenario, as the implementation goal required to achieve the new national development paradigm of green growth. To achieve such a target, it is necessary to diffuse innovative technologies with the capacity to drastically reduce greenhouse gas emissions. To that end, the ripple effect of diffusing innovative technologies on the energy and environment must be quantitatively analyzed using an energy system analysis model such as the MARKAL (Market Allocation) model. However, energy system analysis models based on an optimization methodology have certain limitations in that a technology with superior cost competitiveness dominates the whole market and non-cost factors cannot be considered. Therefore, this study proposes a new methodology for overcoming problems associated with the use of MARKAL models, by interfacing with a forecasting model based on the discrete-choice model. The new methodology was applied to green car technology to verify its usefulness and to study the ripple effects of green car technology on greenhouse gas reduction. The results of this study can be used as a reference when establishing a strategy for effectively reducing greenhouse gas emissions in the transportation sector, and could be of assistance to future studies using the energy system analysis model.

Duk Hee Lee; Sang Yong Park; Jong Chul Hong; Sang Jin Choi; Jong Wook Kim

2013-01-01T23:59:59.000Z

16

Analysis and Synthesis of Load Forecasting Data for Renewable Integration Studies: Preprint  

SciTech Connect (OSTI)

As renewable energy constitutes greater portions of the generation fleet, the importance of modeling uncertainty as part of integration studies also increases. In pursuit of optimal system operations, it is important to capture not only the definitive behavior of power plants, but also the risks associated with systemwide interactions. This research examines the dependence of load forecast errors on external predictor variables such as temperature, day type, and time of day. The analysis was utilized to create statistically relevant instances of sequential load forecasts with only a time series of historic, measured load available. The creation of such load forecasts relies on Bayesian techniques for informing and updating the model, thus providing a basis for networked and adaptive load forecast models in future operational applications.

Steckler, N.; Florita, A.; Zhang, J.; Hodge, B. M.

2013-11-01T23:59:59.000Z

17

Modeling of Uncertainty in Wind Energy Forecast  

E-Print Network [OSTI]

regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

18

A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION  

E-Print Network [OSTI]

in the realm of solar radiation forecasting. In this work, two forecasting models: Autoregressive Moving1 A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION. The very first results show an improvement brought by this approach. 1. INTRODUCTION Solar radiation

Boyer, Edmond

19

Application of a Combination Forecasting Model in Logistics Parks' Demand  

Science Journals Connector (OSTI)

Logistics parks’ demand is an important basis of establishing the development policy of logistics industry and logistics infrastructure for planning. In order to improve the forecast accuracy of logistics parks’ demand, a combination forecasting ... Keywords: Logistics parks' demand, combine, simulated annealing algorithm, grey forecast model, exponential smoothing method

Chen Qin; Qi Ming

2010-05-01T23:59:59.000Z

20

Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.  

SciTech Connect (OSTI)

We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M. (Mathematics and Computer Science); (Univ. of Chicago); (New York Univ.)

2009-10-09T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Short-term solar irradiance forecasting using exponential smoothing state space model  

Science Journals Connector (OSTI)

Abstract We forecast high-resolution solar irradiance time series using an exponential smoothing state space (ESSS) model. To stationarize the irradiance data before applying linear time series models, we propose a novel Fourier trend model and compare the performance with other popular trend models using residual analysis and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) stationarity test. Using the optimized Fourier trend, an ESSS model is implemented to forecast the stationary residual series of datasets from Singapore and Colorado, USA. To compare the performance with other time series models, autoregressive integrated moving average (ARIMA), linear exponential smoothing (LES), simple exponential smoothing (SES) and random walk (RW) models are tested using the same data. The simulation results show that the ESSS model has generally better performance than other time series forecasting models. To assess the reliability of the forecasting model in real-time applications, a complementary study of the forecasting 95% confidence interval and forecasting horizon of the ESSS model has been conducted.

Zibo Dong; Dazhi Yang; Thomas Reindl; Wilfred M. Walsh

2013-01-01T23:59:59.000Z

22

Measuring the forecasting accuracy of models: evidence from industrialised countries  

Science Journals Connector (OSTI)

This paper uses the approach suggested by Akrigay (1989), Tse and Tung (1992) and Dimson and Marsh (1990) to examine the forecasting accuracy of stock price index models for industrialised markets. The focus of this paper is to compare the Mean Absolute Percentage Error (MAPE) of three models, that is, the Random Walk model, the Single Exponential Smoothing model and the Conditional Heteroskedastic model with the MAPE of the benchmark Naive Forecast 1 case. We do not evidence that a single model to provide better forecasting accuracy results compared to other models.

Athanasios Koulakiotis; Apostolos Dasilas

2009-01-01T23:59:59.000Z

23

Network Bandwidth Utilization Forecast Model on High Bandwidth Network  

SciTech Connect (OSTI)

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

Yoo, Wucherl; Sim, Alex

2014-07-07T23:59:59.000Z

24

Improving baseline forecasts in a 500-industry dynamic CGE model of the USA.  

E-Print Network [OSTI]

??MONASH-style CGE models have been used to generate baseline forecasts illustrating how an economy is likely to evolve through time. One application of such forecasts… (more)

Mavromatis, Peter George

2013-01-01T23:59:59.000Z

25

A model for short term electric load forecasting  

E-Print Network [OSTI]

A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE, III Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1975 Major... Subject: Electrical Engineering A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE& III Approved as to style and content by: (Chairman of Committee) (Head Depart t) (Member) ;(Me r (Member) (Member) May 1975 ABSTRACT...

Tigue, John Robert

1975-01-01T23:59:59.000Z

26

RACORO Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Daniel Hartsock CIMMS, University of Oklahoma ARM AAF Wiki page Weather Briefings Observed Weather Cloud forecasting models BUFKIT forecast soundings + guidance...

27

A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting  

Science Journals Connector (OSTI)

Abstract Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily.

Zhongyue Su; Jianzhou Wang; Haiyan Lu; Ge Zhao

2014-01-01T23:59:59.000Z

28

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect (OSTI)

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. [Lawrence Berkeley Lab., CA (United States)]|[Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics]|[Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Hwang, R. [Lawrence Berkeley Lab., CA (United States)

1992-02-01T23:59:59.000Z

29

Improved one day-ahead price forecasting using combined time series and artificial neural network models for the electricity market  

Science Journals Connector (OSTI)

The price forecasts embody crucial information for generators when planning bidding strategies to maximise profits. Therefore, generation companies need accurate price forecasting tools. Comparison of neural network and auto regressive integrated moving average (ARIMA) models to forecast commodity prices in previous researches showed that the artificial neural network (ANN) forecasts were considerably more accurate than traditional ARIMA models. This paper provides an accurate and efficient tool for short-term price forecasting based on the combination of ANN and ARIMA. Firstly, input variables for ANN are determined by time series analysis. This model relates the current prices to the values of past prices. Secondly, ANN is used for one day-ahead price forecasting. A three-layered feed-forward neural network algorithm is used for forecasting next-day electricity prices. The ANN model is then trained and tested using data from electricity market of Iran. According to previous studies, in the case of neural networks and ARIMA models, historical demand data do not significantly improve predictions. The results show that the combined ANNâ??ARIMA forecasts prices with high accuracy for short-term periods. Also, it is shown that policy-making strategies would be enhanced due to increased precision and reliability.

Ali Azadeh; Seyed Farid Ghaderi; Behnaz Pourvalikhan Nokhandan; Shima Nassiri

2011-01-01T23:59:59.000Z

30

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect (OSTI)

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. (Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Hwang, R. (Lawrence Berkeley Lab., CA (United States))

1992-02-01T23:59:59.000Z

31

NREL: Energy Analysis - Energy Forecasting and Modeling Staff  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy Forecasting and Modeling Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Geraly Amador Clayton Barrows Greg Brinkman Brian W Bush Stuart Cohen Carolyn Davidson Paul Denholm Victor Diakov Aron Dobos Easan Drury Kelly Eurek Janine Freeman Marissa Hummon Jennie Jorganson Jordan Macknick Trieu Mai David Mulcahy David Palchak Ben Sigrin Daniel Steinberg Patrick Sullivan Aaron Townsend Laura Vimmerstedt Andrew Weekley Owen Zinaman Photo of Clayton Barrows. Clayton Barrows Postdoctoral Researcher Areas of expertise Power system modeling Primary research interests Power and energy systems

32

Exponential smoothing model selection for forecasting  

Science Journals Connector (OSTI)

Applications of exponential smoothing to forecasting time series usually rely on three basic methods: simple exponential smoothing, trend corrected exponential smoothing and a seasonal variation thereof. A common approach to selecting the method appropriate to a particular time series is based on prediction validation on a withheld part of the sample using criteria such as the mean absolute percentage error. A second approach is to rely on the most appropriate general case of the three methods. For annual series this is trend corrected exponential smoothing: for sub-annual series it is the seasonal adaptation of trend corrected exponential smoothing. The rationale for this approach is that a general method automatically collapses to its nested counterparts when the pertinent conditions pertain in the data. A third approach may be based on an information criterion when maximum likelihood methods are used in conjunction with exponential smoothing to estimate the smoothing parameters. In this paper, such approaches for selecting the appropriate forecasting method are compared in a simulation study. They are also compared on real time series from the M3 forecasting competition. The results indicate that the information criterion approaches provide the best basis for automated method selection, the Akaike information criteria having a slight edge over its information criteria counterparts.

Baki Billah; Maxwell L. King; Ralph D. Snyder; Anne B. Koehler

2006-01-01T23:59:59.000Z

33

Probabilistic Forecasts of Wind Speed: Ensemble Model Output Statistics  

E-Print Network [OSTI]

. Over the past two decades, ensembles of numerical weather prediction (NWP) models have been developed and phrases: Continuous ranked probability score; Density forecast; Ensem- ble system; Numerical weather prediction; Heteroskedastic censored regression; Tobit model; Wind energy. 1 #12;1 Introduction Accurate

Washington at Seattle, University of

34

CCPP-ARM Parameterization Testbed Model Forecast Data  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

Klein, Stephen

35

Application of the Stretched Exponential Production Decline Model to Forecast Production in Shale Gas Reservoirs  

E-Print Network [OSTI]

Production forecasting in shale (ultra-low permeability) gas reservoirs is of great interest due to the advent of multi-stage fracturing and horizontal drilling. The well renowned production forecasting model, Arps? Hyperbolic Decline Model...

Statton, James Cody

2012-07-16T23:59:59.000Z

36

A GIS tool for the evaluation of the precipitation forecasts of a numerical weather prediction model using satellite data  

Science Journals Connector (OSTI)

In this study, the possibility of implementing Geographic Information Systems (GIS) for developing an integrated and automatic operational system for the real-time evaluation of the precipitation forecasts of the numerical weather prediction model BOLAM (BOlogna Limited Area Model) in Greece, is examined. In fact, the precipitation estimates derived by an infrared satellite technique are used for real-time qualitative and quantitative verification of the precipitation forecasts of the model BOLAM through the use of a GIS tool named as precipitation forecasts evaluator (PFE). The application of the developed tool in a case associated with intense precipitation in Greece, suggested that PFE could be a very important support tool for nowcasting and very short-range forecasting of such events.

Haralambos Feidas; Themistoklis Kontos; Nikolaos Soulakellis; Konstantinos Lagouvardos

2007-01-01T23:59:59.000Z

37

A FORECAST MODEL OF AGRICULTURAL AND LIVESTOCK PRODUCTS PRICE  

E-Print Network [OSTI]

A FORECAST MODEL OF AGRICULTURAL AND LIVESTOCK PRODUCTS PRICE Wensheng Zhang1,* , Hongfu Chen1 and excessive fluctuation of agricultural and livestock products price is not only harmful to residents' living, but also affects CPI (Consumer Price Index) values, and even leads to social crisis, which influences

Boyer, Edmond

38

A fully automated and integrated multi-scale forecasting scheme for emergency preparedness  

Science Journals Connector (OSTI)

In this paper, we present one multi-scale integrated simulation technology for emergency preparedness with a holistic approach in hurricane, related storm surge and flood forecasting; infrastructure assessment; and emergency planning. This is an emergency ... Keywords: Finite element, Fully automated through scripting, Multi-scale hurricane simulation, Overland flow, Parallel computation, Water surge

Muhammad Akbar; Shahrouz Aliabadi; Reena Patel; Marvin Watts

2013-01-01T23:59:59.000Z

39

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

SciTech Connect (OSTI)

Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

2011-03-28T23:59:59.000Z

40

Modelling and forecasting Oman crude oil prices using Box-Jenkins techniques  

Science Journals Connector (OSTI)

The Box-Jenkins' Auto Regressive Integrated Moving Average (ARIMA) modelling approach has been applied for the time series analysis of monthly average prices of Oman crude oil taken over a period of 10 years. Several seasonal and non-seasonal ARIMA models were identified. These models were then estimated and compared for their adequacy using the significance of the parameter estimates, mean square errors and Modified Box-Pierce (Ljung-Box) Chi-Square statistic. Based on these criterion a multiplicative seasonal model of the form ARIMA (1,1,5)x(1,1,1) was recommended for short term forecasting.

M.I. Ahmad

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Forecast Calls for Better Models: Examining the Core  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Forecast Calls for Better Models: Examining the Core Forecast Calls for Better Models: Examining the Core Components of Arctic Clouds to Clear Their Influence on Climate For original submission and image(s), see ARM Research Highlights http://www.arm.gov/science/highlights/ Research Highlight Predicting how atmospheric aerosols influence cloud formation and the resulting feedback to climate is a challenge that limits the accuracy of atmospheric models. This is especially true in the Arctic, where mixed-phase (both ice- and liquid-based) clouds are frequently observed, but the processes that determine their composition are poorly understood. To obtain a closer look at what makes up Arctic clouds, scientists characterized cloud droplets and ice crystals collected at the North Slope of Alaska as part of the Indirect and Semi-Direct Aerosol Campaign (ISDAC) field study

42

Continuous Model Updating and Forecasting for a Naturally Fractured Reservoir  

E-Print Network [OSTI]

CONTINUOUS MODEL UPDATING AND FORECASTING FOR A NATURALLY FRACTURED RESERVOIR A Thesis by HISHAM HASSAN S. ALMOHAMMADI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... guidance and support throughout my time here in Texas A&M University. I also would like to thank my committee members, Dr. Eduardo Gildin and Dr. Michael Sherman, for providing valued insight and help during the course of this research. I am indebted...

Almohammadi, Hisham

2013-07-26T23:59:59.000Z

43

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network [OSTI]

for the information in this report; nor does any party represent that the uses of this information will not infringe of transportation fuel and crude oil import requirements to establish the quantitative baseline to support its fuels, integration of energy use and land use planning, and transportation fuel infrastructure

44

Wind and Load Forecast Error Model for Multiple Geographically Distributed Forecasts  

SciTech Connect (OSTI)

The impact of wind and load forecast errors on power grid operations is frequently evaluated by conducting multi-variant studies, where these errors are simulated repeatedly as random processes based on their known statistical characteristics. To generate these errors correctly, we need to reflect their distributions (which do not necessarily follow a known distribution law), standard deviations, auto- and cross-correlations. For instance, load and wind forecast errors can be closely correlated in different zones of the system. This paper introduces a new methodology for generating multiple cross-correlated random processes to simulate forecast error curves based on a transition probability matrix computed from an empirical error distribution function. The matrix will be used to generate new error time series with statistical features similar to observed errors. We present the derivation of the method and present some experimental results by generating new error forecasts together with their statistics.

Makarov, Yuri V.; Reyes Spindola, Jorge F.; Samaan, Nader A.; Diao, Ruisheng; Hafen, Ryan P.

2010-11-02T23:59:59.000Z

45

Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model  

E-Print Network [OSTI]

An important determinant of our energy future is the rate at which energy conservation technologies, once developed, are put into use. At Synergic Resources Corporation, we have adapted and applied a methodology to forecast the use of conservation...

Lang, K.

1982-01-01T23:59:59.000Z

46

Crude oil prices and petroleum inventories : remedies for a broken oil price forecasting model.  

E-Print Network [OSTI]

??The empirical relationship between crude oil prices and petroleum inventories has been exploited in a number of short-term oil price forecasting models. Some of the… (more)

Grimstad, Dan

2007-01-01T23:59:59.000Z

47

Log-normal distribution based EMOS models for probabilistic wind speed forecasting  

E-Print Network [OSTI]

Ensembles of forecasts are obtained from multiple runs of numerical weather forecasting models with different initial conditions and typically employed to account for forecast uncertainties. However, biases and dispersion errors often occur in forecast ensembles, they are usually under-dispersive and uncalibrated and require statistical post-processing. We present an Ensemble Model Output Statistics (EMOS) method for calibration of wind speed forecasts based on the log-normal (LN) distribution, and we also show a regime-switching extension of the model which combines the previously studied truncated normal (TN) distribution with the LN. Both presented models are applied to wind speed forecasts of the eight-member University of Washington mesoscale ensemble, of the fifty-member ECMWF ensemble and of the eleven-member ALADIN-HUNEPS ensemble of the Hungarian Meteorological Service, and their predictive performances are compared to those of the TN and general extreme value (GEV) distribution based EMOS methods an...

Baran, Sándor

2014-01-01T23:59:59.000Z

48

Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction  

E-Print Network [OSTI]

from numerical weather prediction models, which is based on a state-of-the-art circular-processing techniques for forecasts from numerical weather prediction models tend to become ineffective or inapplicableBias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction Le

Washington at Seattle, University of

49

Evaluating the ability of a numerical weather prediction model to forecast tracer concentrations during ETEX 2  

E-Print Network [OSTI]

Evaluating the ability of a numerical weather prediction model to forecast tracer concentrations an operational numerical weather prediction model to forecast air quality are also investigated. These potential a numerical weather prediction (NWP) model independently of the CTM. The NWP output is typically archived

Dacre, Helen

50

HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson  

E-Print Network [OSTI]

and decision makers strongly rely on Numerical Weather Prediction (NWP) models, for example on the forecasted on forecasted precipitation. KEYWORDS: Numerical weather prediction models, validation, precipitation 1. INTRODUCTION Numerical Weather Prediction (NWP) models are widely used by avalanche practitioners. Their de

Jamieson, Bruce

51

FY 1996 solid waste integrated life-cycle forecast characteristics summary. Volumes 1 and 2  

SciTech Connect (OSTI)

For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters. The range is primarily due to uncertainties associated with the Tank Waste Remediation System (TWRS) program, including uncertainties regarding retrieval of long-length equipment, scheduling, and tank retrieval technologies.

Templeton, K.J.

1996-05-23T23:59:59.000Z

52

An Evaluation of Tropical Cyclone Genesis Forecasts from Global Numerical Models  

Science Journals Connector (OSTI)

Tropical cyclone (TC) forecasts rely heavily on output from global numerical models. While considerable research has investigated the skill of various models with respect to track and intensity, few studies have considered how well global models ...

Daniel J. Halperin; Henry E. Fuelberg; Robert E. Hart; Joshua H. Cossuth; Philip Sura; Richard J. Pasch

2013-12-01T23:59:59.000Z

53

Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA  

SciTech Connect (OSTI)

In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing “quasi-deterministic” components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

Hou, Zhangshuan; Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.

2014-10-27T23:59:59.000Z

54

AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.  

E-Print Network [OSTI]

AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

Povinelli, Richard J.

55

Amending Numerical Weather Prediction forecasts using GPS  

E-Print Network [OSTI]

. Satellite images and Numerical Weather Prediction (NWP) models are used together with the synoptic surfaceAmending Numerical Weather Prediction forecasts using GPS Integrated Water Vapour: a case study to validate the amounts of humidity in Numerical Weather Prediction (NWP) model forecasts. This paper presents

Stoffelen, Ad

56

Application of Improved Grey Model in Long-term Load Forecasting of Power Engineering  

Science Journals Connector (OSTI)

Grey model is usually been used for long-term load forecasting in power engineering, but it has significant limitations. If the moving average method and Markov model are connected with grey model, the accuracy of this improved grey model used for long-term load forecasting in power engineering can be effectively increased. In this paper, ordinary grey model and improved grey model are all chosen and used for long-term power load forecasting in power engineering, and the power load data of Qingdao in the past decade is selected for the analysis. The result of the analysis shows that the accuracy of improved grey model is significant higher than ordinary model, so the improved grey model can be used for long-term load forecasting in power engineering.

Junjie Kang; Huijuan Zhao

2012-01-01T23:59:59.000Z

57

Atmospheric and seeing forecast: WRF model validation with in situ measurements at ORM  

Science Journals Connector (OSTI)

......orographic data to initialize WRF. 6 CONCLUSION For the first time, the WRF model, coupled with the...used to forecast not only local meteorological parameters...relative humidity and wind speed at ground level...simultaneous forecasts, the WRF-in situ instrument agreement......

C. Giordano; J. Vernin; H. Vázquez Ramió; C. Muñoz-Tuñón; A. M. Varela; H. Trinquet

2013-01-01T23:59:59.000Z

58

Precipitation Forecasting with Gamma Distribution Models for Gridded Precipitation Events in Eastern Oklahoma and Northwest Arkansas  

Science Journals Connector (OSTI)

An elegant and easy to implement probabilistic quantitative precipitation forecasting model that can be used to estimate the probability of exceedance (POE) is presented. The model was built using precipitation data collected across eastern ...

Steven A. Amburn; Andrew S.I.D. Lang; Michael A. Buonaiuto

59

Generalized Additive Models versus Linear Regression in Generating Probabilistic MOS Forecasts of Aviation Weather Parameters  

Science Journals Connector (OSTI)

The skill of probabilistic Model Output Statistics forecasts generated from Generalized Additive Models (GAM) is compared to that of traditional multiple linear regression techniques. Unlike linear regression, where each predictor term in the ...

Robert L. Vislocky; J. Michael Fritsch

1995-12-01T23:59:59.000Z

60

Using a Business Process Model as a Central Organizing Construct for an Undergraduate Weather Forecasting Course  

Science Journals Connector (OSTI)

For the last five years, the author has employed a business process model as a central organizing construct for the senior-level Forecasting Techniques course at Embry- Riddle Aeronautical University's Daytona Beach, Florida, campus. The process model ...

John M. Lanicci

2012-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

FY 1996 solid waste integrated life-cycle forecast container summary volume 1 and 2  

SciTech Connect (OSTI)

For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the containers expected to be used for these waste shipments from 1996 through the remaining life cycle of the Hanford Site. In previous years, forecast data have been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to the more detailed report on waste volumes: WHC-EP0900, FY 1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary. Both of these documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on the types of containers that will be used for packaging low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major waste generators for each waste category and container type are also discussed. Containers used for low-level waste (LLW) are described in Appendix A, since LLW requires minimal treatment and storage prior to onsite disposal in the LLW burial grounds. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste are expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters.

Valero, O.J.

1996-04-23T23:59:59.000Z

62

PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico | Open  

Open Energy Info (EERE)

Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Jump to: navigation, search Name PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Agency/Company /Organization Pacific Northwest National Laboratory Sector Energy Topics Co-benefits assessment, - Environmental and Biodiversity, - Health, Background analysis Resource Type Publications Website http://www.pnl.gov/atmospheric Country Mexico UN Region Latin America and the Caribbean References PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico[1] PNNL Publications on WRF-Chem modeling in Mexico include: Fast JD, M Shrivastava, RA Zaveri, and JC. Barnard. 2010. "Modeling particulates and direct radiative forcing from urban to synoptic scales downwind of Mexico City." Annual European Geosciences Union Assembly,

63

Chemistry, Reservoir, and Integrated Models  

Broader source: Energy.gov [DOE]

Below are the project presentations and respective peer review results for Chemistry, Reservoir and Integrated Models.

64

Wind Power Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email List Self Supplied Balancing Reserves Dynamic...

65

Forecasting Volatility in Stock Market Using GARCH Models  

E-Print Network [OSTI]

Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive ...

Yang, Xiaorong

2008-01-01T23:59:59.000Z

66

Radiation fog forecasting using a 1-dimensional model  

E-Print Network [OSTI]

measuring site (Molly Caren), the soil moisture measuring site (Wilmington), and (b) location of the forecast site (Ohio River Basin near Cincinnati including Lunken airport) . . 23 3 An example of a COBEL configuration file for 25 August 1996, showing... measuring site (Molly Caren), the soil moisture measuring site (Wilmington), and (b) location of the forecast site (Ohio River Basin near Cincinnati including Lunken airport) . . 23 3 An example of a COBEL configuration file for 25 August 1996, showing...

Peyraud, Lionel

2012-06-07T23:59:59.000Z

67

An Evaluation of Decadal Probability Forecasts from State-of-the-Art Climate Models  

Science Journals Connector (OSTI)

While state-of-the-art models of Earth's climate system have improved tremendously over the last 20 years, nontrivial structural flaws still hinder their ability to forecast the decadal dynamics of the Earth system realistically. Contrasting the ...

Emma B. Suckling; Leonard A. Smith

2013-12-01T23:59:59.000Z

68

Research on the risk forecast model in the coal mine system based on GSPA-Markov  

Science Journals Connector (OSTI)

Safety accidents in the coal mine occurred frequently, that how to reduce them became an important national task, which the hazards identification and the risk forecast work in the coal mine system can solve. In the process of risk forecast in the coal mine system, considering characteristics that system risk is different in different period, the IDO (identification, difference, opposition) change rule of the set pair which has element weight is analyzed, and on the basis of which, the system risk forecast model based on GSPA-MARKOV is put forward. The application example shows that the risk state in the coal mine system is forecasted by the transition probability and the ergodicity in the model, which embodies fully dynamic, predictable and so on , thus it provides a new method to determine the risk state in the coal mine system.

LI De-shun; XU Kai-li

2011-01-01T23:59:59.000Z

69

Increasing NOAA's computational capacity to improve global forecast modeling  

E-Print Network [OSTI]

competing numerical weather prediction centers such as the European Center for MediumRange Weather Forecasts (ECMWF). For most sensibleweather metrics, we lag 1 to 1.5 days (i.e., they make a 3.5day of NOAA's current investment in weather satellites. Without a modern data assimilation system

Hamill, Tom

70

An Improved Adaptive Exponential Smoothing Model for Short-term Travel Time Forecasting of Urban Arterial Street  

Science Journals Connector (OSTI)

Short-term forecasting of travel time is essential for the success of intelligent transportation system. In this paper, we review the state-of-art of short-term traffic forecasting models and outline their basic ideas, related works, advantages and disadvantages of each model. An improved adaptive exponential smoothing (IAES) model is also proposed to overcome the drawbacks of the previous adaptive exponential smoothing model. Then, comparing experiments are carried out under normal traffic condition and abnormal traffic condition to evaluate the performance of four main branches of forecasting models on direct travel time data obtained by license plate matching (LPM). The results of experiments show each model seems to have its own strength and weakness. The forecasting performance of IASE is superior to other models in shorter forecasting horizon (one and two step forecasting) and the IASE is capable of dealing with all kind of traffic conditions.

Zhi-Peng LI; Hong YU; Yun-Cai LIU; Fu-Qiang LIU

2008-01-01T23:59:59.000Z

71

A hybrid dynamic and fuzzy time series model for mid-term power load forecasting  

Science Journals Connector (OSTI)

Abstract A new hybrid model for forecasting the electric power load several months ahead is proposed. To allow for distinct responses from individual load sectors, this hybrid model, which combines dynamic (i.e., air temperature dependency of power load) and fuzzy time series approaches, is applied separately to the household, public, service, and industrial sectors. The hybrid model is tested using actual load data from the Seoul metropolitan area, and its predictions are compared with those from two typical dynamic models. Our investigation shows that, in the case of four-month forecasting, the proposed model gives the actual monthly power load of every sector with only less than 3% absolute error and satisfactory reduction of forecasting errors compared to other models from previous studies.

Woo-Joo Lee; Jinkyu Hong

2015-01-01T23:59:59.000Z

72

Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database  

E-Print Network [OSTI]

Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use have come to expect. Potato late blight risk models were some of the earliest weather-based models. This analysis compares two types of potato late blight risk models that were originally trained on location

Douches, David S.

73

An Improved Model To Forecast Co2 Leakage Rates Along A Wellbore | Open  

Open Energy Info (EERE)

Model To Forecast Co2 Leakage Rates Along A Wellbore Model To Forecast Co2 Leakage Rates Along A Wellbore Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article: An Improved Model To Forecast Co2 Leakage Rates Along A Wellbore Details Activities (0) Areas (0) Regions (0) Abstract: Large-scale geological storage of CO2 is likely to bring CO2 plumes into contact with a large number of existing wellbores. Wellbores that no longer provide proper zonal isolation establish a primary pathway for a buoyant CO2-rich phase to escape from the intended storage formation. The hazard of CO2 leakage along these pathways will depend on the rate of leakage. Thus a useful component of a risk assessment framework is a model of CO2 leakage. Predicting the flux of CO2 along a leaking wellbore requires a model of fluid properties and of transport along the leakage

74

Integrated astrophysical modeling  

SciTech Connect (OSTI)

In this project, we have developed prototype techniques for defining and extending a variety of astrophysical modeling capabilities, including those involving multidimensional hydrodynamics, complex transport, and flexibly-coupled equation-of state and nuclear reaction networks. As expected, this project is having both near-term payoffs in understanding complex astrophysical phenomena, as well as significant spin-offs in terms of people and ideas to related ASCI code efforts. Most of our work in the first part of this project was focused on the modularization, extension, and initial integration of 4 previously separate and incommensurate codes: the stellar evolution/explosion code KEPLER; the non-LTE spectral line transport code, EDDINGTON, used for modeling supernovae spectra; the 3-D smooth particle hydro code, PIP; and the discontinuous-finite-element, 3D hydro module from the lCF3D code.

Weaver, T.A., Eastman, R.G., Dubois, P., Eltgroth, P.G., Gentile, N., Jedamzik, K., Wilson, J.R.

1997-06-03T23:59:59.000Z

75

Joint Seasonal ARMA Approach for Modeling of Load Forecast Errors in Planning Studies  

SciTech Connect (OSTI)

To make informed and robust decisions in the probabilistic power system operation and planning process, it is critical to conduct multiple simulations of the generated combinations of wind and load parameters and their forecast errors to handle the variability and uncertainty of these time series. In order for the simulation results to be trustworthy, the simulated series must preserve the salient statistical characteristics of the real series. In this paper, we analyze day-ahead load forecast error data from multiple balancing authority locations and characterize statistical properties such as mean, standard deviation, autocorrelation, correlation between series, time-of-day bias, and time-of-day autocorrelation. We then construct and validate a seasonal autoregressive moving average (ARMA) model to model these characteristics, and use the model to jointly simulate day-ahead load forecast error series for all BAs.

Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.; Diao, Ruisheng; Lu, Ning

2014-04-14T23:59:59.000Z

76

Generating and Calibrating Probabilistic Quantitative Precipitation Forecasts from the High-Resolution NWP Model COSMO-DE  

Science Journals Connector (OSTI)

Statistical postprocessing is an integral part of an ensemble prediction system. This study compares methods used to derive probabilistic quantitative precipitation forecasts based on the high-resolution version of the German-focused Consortium ...

Sabrina Bentzien; Petra Friederichs

2012-08-01T23:59:59.000Z

77

Wind Power Forecasting  

Science Journals Connector (OSTI)

The National Center for Atmospheric Research (NCAR) has configured a Wind Power Forecasting System for Xcel Energy that integrates high resolution and ensemble...

Sue Ellen Haupt; William P. Mahoney; Keith Parks

2014-01-01T23:59:59.000Z

78

Forecasting a Moving Target: Ensemble Models for ILI Case Count Predictions Prithwish Chakraborty  

E-Print Network [OSTI]

with official flu estimates. We also compare the prediction accuracy between model-level fusion of differentForecasting a Moving Target: Ensemble Models for ILI Case Count Predictions Prithwish Chakraborty using neighbor- hood embedding to predict flu case counts. Comparing our proposed ensemble method

Ryder, Barbara G.

79

Impact of large scale circulation on European summer surface ozone and consequences for modelling forecast  

E-Print Network [OSTI]

of using day-to-day varying chemical boundary conditions produced by a global chemical weather forecast platform instead of climatological monthly means at the frontiers of a regional model. We performed two- transport models (CTMs) that represent physical and chemical processes controlling ozone concentrations

Menut, Laurent

80

Evaluation of Advanced Wind Power Forecasting Models Results of the Anemos Project  

E-Print Network [OSTI]

1 Evaluation of Advanced Wind Power Forecasting Models ­ Results of the Anemos Project I. Martí1.kariniotakis@ensmp.fr Abstract An outstanding question posed today by end-users like power system operators, wind power producers or traders is what performance can be expected by state-of-the-art wind power prediction models. This paper

Paris-Sud XI, Université de

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Global and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting  

E-Print Network [OSTI]

and substorms; 2784 Magnetospheric Physics: Solar wind/magnetosphere interactions; 3210 Mathematical Geophysics in the solar wind-magnetosphere interaction, de- veloping first principles models that encompass allGlobal and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting

Sitnov, Mikhail I.

82

Research of least squares support vector regression based on differential evolution algorithm in short-term load forecasting model  

Science Journals Connector (OSTI)

To improve the accuracy of short-term load forecasting a differential evolution algorithm (DE) based least squares support vector regression (LSSVR) method is proposed in this paper. Through optimizing the regularization parameter and kernel parameter of the LSSVR by DE a short-term load forecasting model which can take load affected factors such as meteorology weather and date types into account is built. The proposed LSSVR method is proved by implementing short-term load forecasting on the real historical data of Yangquan power system in China. The average forecasting error is less than 1.6% which shows better accuracy and stability than the traditional LSSVR and Support vector regression. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system more efficiently.

2014-01-01T23:59:59.000Z

83

Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models  

Science Journals Connector (OSTI)

Ukraine is one of the most developed agriculture countries and one of the biggest crop producers in the world. Timely and accurate crop yield forecasts for Ukraine at regional level become a key element in providing support to policy makers in food security. In this paper, feasibility and relative efficiency of using moderate resolution satellite data to winter wheat forecasting in Ukraine at oblast level is assessed. Oblast is a sub-national administrative unit that corresponds to the NUTS2 level of the Nomenclature of Territorial Units for Statistics (NUTS) of the European Union. NDVI values were derived from the MODIS sensor at the 250 m spatial resolution. For each oblast NDVI values were averaged for a cropland map (Rainfed croplands class) derived from the ESA GlobCover map, and were used as predictors in the regression models. Using a leave-one-out cross-validation procedure, the best time for making reliable yield forecasts in terms of root mean square error was identified. For most oblasts, NDVI values taken in April–May provided the minimum RMSE value when comparing to the official statistics, thus enabling forecasts 2–3 months prior to harvest. The NDVI-based approach was compared to the following approaches: empirical model based on meteorological observations (with forecasts in April–May that provide minimum RMSE value) and WOFOST crop growth simulation model implemented in the CGMS system (with forecasts in June that provide minimum RMSE value). All three approaches were run to produce winter wheat yield forecasts for independent datasets for 2010 and 2011, i.e. on data that were not used within model calibration process. The most accurate predictions for 2010 were achieved using the CGMS system with the RMSE value of 0.3 t ha?1 in June and 0.4 t ha?1 in April, while performance of three approaches for 2011 was almost the same (0.5–0.6 t ha?1 in April). Both NDVI-based approach and CGMS system overestimated winter wheat yield comparing to official statistics in 2010, and underestimated it in 2011. Therefore, we can conclude that performance of empirical NDVI-based regression model was similar to meteorological and CGMS models when producing winter wheat yield forecasts at oblast level in Ukraine 2–3 months prior to harvest, while providing minimum requirements to input datasets.

Felix Kogan; Nataliia Kussul; Tatiana Adamenko; Sergii Skakun; Oleksii Kravchenko; Oleksii Kryvobok; Andrii Shelestov; Andrii Kolotii; Olga Kussul; Alla Lavrenyuk

2013-01-01T23:59:59.000Z

84

Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia  

E-Print Network [OSTI]

values were driven mainly by WRF errors in wind speed simulation. However, in both cases the qualityFire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia from 1985 to 2009 has been simulated using the Weather Research and Forecasting (WRF) model

Evans, Jason

85

An Examination of the Uncertainty in Interpolated Winds and Its Effect on the Validation and Intercomparison of Forecast Models  

Science Journals Connector (OSTI)

Meteorological models need to be compared to long-term, routinely collected meteorological data. Whenever numerical forecast models are validated and compared, verification winds are normally interpolated to individual model grid points. To be ...

J. Scott Greene; W. Ethan Cook; David Knapp; Patrick Haines

2002-03-01T23:59:59.000Z

86

The MAGS Integrated Modeling System  

Science Journals Connector (OSTI)

The Mackenzie GEWEX Study (MAGS) integrated modeling system was developed to couple, with full feedback, selected atmospheric and hydrologic models, with the expectation that the imposed consistency will enhan...

E. D. (Ric) Soulis; Frank R. Seglenieks

2008-01-01T23:59:59.000Z

87

A COMPARISON OF CLOUD MICROPHYSICAL QUANTITIES WITH FORECASTS FROM CLOUD PREDICTION MODELS  

E-Print Network [OSTI]

of the Atmospheric System Research (ASR) Program, Bethesda, MD March 15-19, 2010 Environmental Sciences Department/Atmospheric Plains (SGP) site. Cloud forecasts generated by the models are compared with cloud microphysical and radiosonde) are used to derive the cloud microphysical quantities: ice water content, liquid water content

88

USING SATELLITE OBSERVATIONS AND REANALYSES TO EVALUATE CLIMATE AND WEATHER FORECAST MODELS  

E-Print Network [OSTI]

USING SATELLITE OBSERVATIONS AND REANALYSES TO EVALUATE CLIMATE AND WEATHER FORECAST MODELS Richard Email: rpa@mail.nerc-essc.ac.uk ABSTRACT Satellite observations of water vapour and radiative fluxes are used in combination with reanalyses data to evaluate the Met Office weather and climate prediction

Allan, Richard P.

89

Multi-objective calibration of forecast ensembles using Bayesian model averaging  

E-Print Network [OSTI]

weather prediction models. The BMA predictive probability density function (PDF) of any weather quantity but complementary metrics of forecast skill, and uses a numerical algorithm to solve for the Pareto set of parameters that have consistently good performance across multiple performance metrics. Two illustrative case

Vrugt, Jasper A.

90

Current challenges using models to forecast seawater intrusion: lessons from the Eastern Shore of Virginia, USA  

E-Print Network [OSTI]

Current challenges using models to forecast seawater intrusion: lessons from the Eastern Shore of seawater intrusion from natural and anthropo- genic causes. The characteristics of transition zones between. Computer speed and storage capabilities have increased dramatically in the last few decades, to the point

91

Seasonal Maize Forecasting for South Africa and Zimbabwe Derived from an Agroclimatological Model  

E-Print Network [OSTI]

Seasonal Maize Forecasting for South Africa and Zimbabwe Derived from an Agroclimatological Model, with a hindcast correlation over 16 seasons of 0.92 for South Africa and 0.62 for Zimbabwe. Over 17 seasons and actual maize water-stress in South Africa, and a correlation of 0.79 for the same relationship

Martin, Randall

92

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics  

E-Print Network [OSTI]

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics MAURICE J. SCHMEITS, KEES J. KOK, AND DAAN H. P. VOGELEZANG Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands (Manuscript received 29 April 2004, in final form 7 September 2004

Schmeits, Maurice

93

Artificial neural network based models for forecasting electricity generation of grid connected solar PV power plant  

Science Journals Connector (OSTI)

This paper presents an artificial neural network (ANN) approach for forecasting the performance of electric energy generated output from a working 25-kWp grid connected solar PV system and a 100-kWp grid connected PV system installed at Minicoy Island of Union Territory of Lakshadweep Islands. The ANN interpolates among the solar PV generation output and relevant parameters such as solar radiation, module temperature and clearness index. In this study, three ANN models are implemented and validated with reasonable accuracy on real electric energy generation output data. The first model is univariate based on solar radiation and the output values. The second model is a multivariate model based on module temperature along with solar radiation. The third model is also a multivariate model based on module temperature, solar radiation and clearness index. A forecasting performance measure such as percentage root mean square error has been presented for each model. The second model, which gives the most accurate results, has been used in forecasting the generation output for another PV system with similar accuracy.

Imtiaz Ashraf; A. Chandra

2004-01-01T23:59:59.000Z

94

Evaluation of Forecasted Southeast Pacific Stratocumulus in the NCAR, GFDL and ECMWF Models  

SciTech Connect (OSTI)

We examine forecasts of Southeast Pacific stratocumulus at 20S and 85W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3 days to determine the differences with the EPIC field data. Observations during the EPIC cruise show a stable and well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the four models is that the forecasted planetary boundary layer (PBL) height is too low when compared to EPIC observations. All the models produce a strong diurnal cycle in the Liquid Water Path (LWP) but there are large differences in the amplitude and the phase compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface. There is a large spread in the surface energy budget terms amongst the models and large discrepancies with observational estimates. Single Column Model (SCM) experiments with the CAM show that the vertical pressure velocity has a large impact on the PBL height and LWP. Both the amplitude of the vertical pressure velocity field and its vertical structure play a significant role in the collapse or the maintenance of the PBL.

Hannay, C; Williamson, D L; Hack, J J; Kiehl, J T; Olson, J G; Klein, S A; Bretherton, C S; K?hler, M

2008-01-24T23:59:59.000Z

95

Modeling and Analysis Papers - Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation > Table 1 Evaluation > Table 1 Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to 2002 Average Absolute Percent Error Variable AEO82 to AEO97 AEO82 to AEO98 AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 Consumption Total Energy Consumption 1.6 1.7 1.7 1.8 1.9 1.9 Total Petroleum Consumption 2.8 2.9 2.8 2.9 3.0 2.9 Total Natural Gas Consumption 5.8 5.7 5.6 5.6 5.5 5.5 Total Coal Consumption 2.7 3.0 3.2 3.3 3.5 3.6 Total Electricity Sales 1.6 1.7 1.8 1.9 2.4 2.5 Production Crude Oil Production 4.2 4.3 4.5 4.5 4.5 4.5 Natural Gas Production 5.0 4.8 4.7 4.6 4.6 4.4 Coal Production 3.7 3.6 3.6 3.5 3.7 3.6 Imports and Exports Net Petroleum Imports 10.1 9.5 8.8 8.4 7.9 7.4 Net Natural Gas Imports 17.4 16.7 16.0 15.9 15.8 15.8 Net Coal Exports

96

A New Forecasting Model for USD/CNY Exchange Rate  

E-Print Network [OSTI]

This paper models the return series of USD/CNY exchange rate by considering the conditional mean and conditional volatility simultaneously. An index type functional-coefficient model is adopted to model the conditional ...

Cai, Zongwu; Chen, Linna; Fang, Ying

2012-09-18T23:59:59.000Z

97

HEURISTIC APPROACH FOR OPTIMAL PARAMETER ESTIMATION OF ELECTRIC LOAD FORECAST MODEL  

Science Journals Connector (OSTI)

Load forecasting is a crucial aspect of electric power system planning and operation. This paper presents a heuristic approach for optimal parameter estimation of long term load forecast models. The problem is viewed as an optimization one in which the goal is to minimize the total estimation error by properly adjusting the model coefficients. A particle swarm optimization algorithm is developed to minimize the error associated with the estimated model parameters. Real data of Egyptian network is used to perform this study. Results are reported and compared to those obtained using the well known least error squares estimation technique. Comparison results are in favor of the proposed approach which signifies its potential as a promising estimation tool.

M. R. AlRashidi; K. M. EL?Naggar

2009-01-01T23:59:59.000Z

98

A model for improving ocean wind forecasts using satellite  

E-Print Network [OSTI]

Using the dynamical model from previous talk we now want to assimilate the satellite measurements Using the dynamical model from previous talk we now want to assimilate the satellite measurements now want to assimilate the satellite measurements into this model. We will discuss the measurement

Malmberg, Anders

99

Regional forecasting with global atmospheric models; Final report  

SciTech Connect (OSTI)

The purpose of the project was to conduct model simulations for past and future climate change with respect to the proposed Yucca Mtn. repository. The authors report on three main topics, one of which is boundary conditions for paleo-hindcast studies. These conditions are necessary for the conduction of three to four model simulations. The boundary conditions have been prepared for future runs. The second topic is (a) comparing the atmospheric general circulation model (GCM) with observations and other GCMs; and (b) development of a better precipitation data base for the Yucca Mtn. region for comparisons with models. These tasks have been completed. The third topic is preliminary assessments of future climate change. Energy balance model (EBM) simulations suggest that the greenhouse effect will likely dominate climate change at Yucca Mtn. for the next 10,000 years. The EBM study should improve rational choice of GCM CO{sub 2} scenarios for future climate change.

Crowley, T.J.; Smith, N.R. [Applied Research Corp., College Station, TX (United States)

1994-05-01T23:59:59.000Z

100

Detecting Dependence in the Sensitive Parameter Space of a Model Using Statistical Inference and Large Forecast Ensembles  

Science Journals Connector (OSTI)

This study looks for evidence of correlation among model physical parameters in the sensitive parameter space defined by those randomly sampled physical parameter vectors that induce the most notable response in some forecast metric. These “...

J. G. McLay; M. Liu

2014-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Evolving an Information Diffusion Model Using a Genetic Algorithm for Monthly River Discharge Time Series Interpolation and Forecasting  

Science Journals Connector (OSTI)

The identification of the rainfall–runoff relationship is a significant precondition for surface–atmosphere process research and operational flood forecasting, especially in inadequately monitored basins. Based on an information diffusion model (...

Chengzu Bai; Mei Hong; Dong Wang; Ren Zhang; Longxia Qian

2014-12-01T23:59:59.000Z

102

Resolved Turbulence Characteristics in Large-Eddy Simulations Nested within Mesoscale Simulations Using the Weather Research and Forecasting Model  

Science Journals Connector (OSTI)

One-way concurrent nesting within the Weather Research and Forecasting Model (WRF) is examined for conducting large-eddy simulations (LES) nested within mesoscale simulations. Wind speed, spectra, and resolved turbulent stresses and turbulence ...

Jeff Mirocha; Branko Kosovi?; Gokhan Kirkil

2014-02-01T23:59:59.000Z

103

Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices  

E-Print Network [OSTI]

This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futures prices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the cr...

Kulkarni, Siddhivinayak

2009-01-01T23:59:59.000Z

104

Quarterly Journal of the Royal Meteorological Society Q. J. R. Meteorol. Soc. 00: 115 (0000) Controlling model error of underdamped forecast models in  

E-Print Network [OSTI]

-dependent predictability, ensemble methods have become popular for producing numerical weather forecasts (Molteni weather prediction or climate dynamics. In such simulations numerical codes tend to produce large errors of the forecast model and a numerical model error due to the choice of the numerical method used to simulate those

Gottwald, Georg A.

105

Solid waste integrated forecast technical (SWIFT) report: FY1997 to FY 2070, Revision 1  

SciTech Connect (OSTI)

This web site provides an up-to-date report on the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons with previous forecasts and with other national data sources. This web site does not include: liquid waste (current or future generation); waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); or waste that has been received by the WM Project to date (i.e., inventory waste). The focus of this web site is on low-level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this web site is reporting data th at was requested on 10/14/96 and submitted on 10/25/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program's life cycle. Therefore, these data represent revisions from the previous FY97.0 Data Version, due primarily to revised estimates from PNNL. There is some useful information about the structure of this report in the SWIFT Report Web Site Overview.

Valero, O.J.; Templeton, K.J.; Morgan, J.

1997-01-07T23:59:59.000Z

106

Separations and safeguards model integration.  

SciTech Connect (OSTI)

Research and development of advanced reprocessing plant designs can greatly benefit from the development of a reprocessing plant model capable of transient solvent extraction chemistry. This type of model can be used to optimize the operations of a plant as well as the designs for safeguards, security, and safety. Previous work has integrated a transient solvent extraction simulation module, based on the Solvent Extraction Process Having Interaction Solutes (SEPHIS) code developed at Oak Ridge National Laboratory, with the Separations and Safeguards Performance Model (SSPM) developed at Sandia National Laboratory, as a first step toward creating a more versatile design and evaluation tool. The goal of this work was to strengthen the integration by linking more variables between the two codes. The results from this integrated model show expected operational performance through plant transients. Additionally, ORIGEN source term files were integrated into the SSPM to provide concentrations, radioactivity, neutron emission rate, and thermal power data for various spent fuels. This data was used to generate measurement blocks that can determine the radioactivity, neutron emission rate, or thermal power of any stream or vessel in the plant model. This work examined how the code could be expanded to integrate other separation steps and benchmark the results to other data. Recommendations for future work will be presented.

Cipiti, Benjamin B.; Zinaman, Owen

2010-09-01T23:59:59.000Z

107

Efficient Modeling and Forecasting of Electricity Spot Prices  

Science Journals Connector (OSTI)

Abstract The increasing importance of renewable energy, especially solar and wind power, has led to new forces in the formation of electricity prices. Hence, this paper introduces an econometric model for the hourly time series of electricity prices of the European Power Exchange (EPEX) which incorporates specific features like renewable energy. The model consists of several sophisticated and established approaches and can be regarded as a periodic VAR-TARCH with wind power, solar power, and load as influences on the time series. It is able to map the distinct and well-known features of electricity prices in Germany. An efficient iteratively reweighted lasso approach is used for the estimation. Moreover, it is shown that several existing models are outperformed by the procedure developed in this paper.

Florian Ziel; Rick Steinert; Sven Husmann

2014-01-01T23:59:59.000Z

108

Bayesian model selection for dark energy using weak lensing forecasts  

Science Journals Connector (OSTI)

......cosmic shear surveys show exceptional...constraining the dark energy equation of state...potential for a survey to constrain dark energy parameters for...The fiducial survey will be able...between dynamical dark energy models and lambdaCDM......

Ivan Debono

2014-01-01T23:59:59.000Z

109

On model selection forecasting, dark energy and modified gravity  

Science Journals Connector (OSTI)

......be achieved with the dark energy survey (DES) (Wester et...considered. DES is the Dark Energy Survey, PS1 is the Pan-STARRS...imaging (weak lensing) surveys should be able decisively distinguish a dark energy GR model from a DGP......

A. F. Heavens; T. D. Kitching; L. Verde

2007-09-21T23:59:59.000Z

110

Evaluation of artificial neural networks as a model for forecasting consumption of wood products  

Science Journals Connector (OSTI)

In specific sciences, such as forest policy, the need for anticipation becomes more urgent because it has to manage valuable natural resources whose protection and sustainable management is rendered essential. In this paper, a modern method has been used, known as artificial neural networks (ANNs). In order to forecast the necessary future volumes of timber in Greece, a neural network has been developed and trained, using a variety of time series derived from the database of the Food and Agriculture Organisation of the United Nations (FAO) (concerning Greece) as external values and as internal value the Consumer Price Index has been used. Comparing the results of this project with linear and non-linear econometric forecasting models, it has been found that neural networks correspond, as confirmed by the econometric indicators MAPE (average absolute percentage error) and RMSE (the square root of the percentage by the average sum of squares differences).

Giorgos Tigas; Panagiotis Lefakis; Konstantinos Ioannou; Athanasios Hasekioglou

2013-01-01T23:59:59.000Z

111

Novel effects of demand side management data on accuracy of electrical energy consumption modeling and long-term forecasting  

Science Journals Connector (OSTI)

Abstract Worldwide implementation of demand side management (DSM) programs has had positive impacts on electrical energy consumption (EEC) and the examination of their effects on long-term forecasting is warranted. The objective of this study is to investigate the effects of historical DSM data on accuracy of EEC modeling and long-term forecasting. To achieve the objective, optimal artificial neural network (ANN) models based on improved particle swarm optimization (IPSO) and shuffled frog-leaping (SFL) algorithms are developed for EEC forecasting. For long-term EEC modeling and forecasting for the U.S. for 2010–2030, two historical data types used in conjunction with developed models include (i) EEC and (ii) socio-economic indicators, namely, gross domestic product, energy imports, energy exports, and population for 1967–2009 period. Simulation results from IPSO-ANN and SFL-ANN models show that using socio-economic indicators as input data achieves lower mean absolute percentage error (MAPE) for long-term EEC forecasting, as compared with EEC data. Based on IPSO-ANN, it is found that, for the U.S. EEC long-term forecasting, the addition of DSM data to socio-economic indicators data reduces MAPE by 36% and results in the estimated difference of 3592.8 MBOE (5849.9 TW h) in EEC for 2010–2030.

F.J. Ardakani; M.M. Ardehali

2014-01-01T23:59:59.000Z

112

Today's Forecast: Improved Wind Predictions | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

113

Today's Forecast: Improved Wind Predictions | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

114

Combining multi-objective optimization and bayesian model averaging to calibrate forecast ensembles of soil hydraulic models  

SciTech Connect (OSTI)

Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multi-objective optimization and Bayesian Model Averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multi-objective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM, and used to generate four different model ensembles. These ensembles are post-processed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are: (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multi-objective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.

Vrugt, Jasper A [Los Alamos National Laboratory; Wohling, Thomas [NON LANL

2008-01-01T23:59:59.000Z

115

Advanced forecast of coal seam thickness variation by integrated geophysical method in the laneway  

Science Journals Connector (OSTI)

Coal seam thickness variation has a direct relationship with coal mine design and mining, and the mutation locations of the thickness are generally the gas accumulation area. In order to justify the feasibility and validity of advanced forecast about the thickness change, we carried out geophysical numerical simulation. Utilizing generalized Radon transform migration, coal-rock interface can be identified with an error of less than 2%. By the calculation of 2.5D finite difference method, transient electric magnetic response characteristics of the thickness variation is conspicuous. In a coal mine the case study indicated that: the reflected wave energy anomaly offer interface information of the thickness change point; the apparent resistivity provide the physical index of the thick or thin coal seam area; synthesizing two kinds of information can predict the thickness variation tendency ahead of the driving face, which can ensure the safety of driving efficiency.

Wang Bo; Liu Sheng-dong; Jiang Zhi-hai; Huang Lan-ying

2011-01-01T23:59:59.000Z

116

Where can I find free economic forecasts? Economic forecasts have become an integral part of business and individual investment decisions. Economic  

E-Print Network [OSTI]

, the Conference Board provides short term (quarterly and annual) forecasts for real GDP, real consumer spending include (among others): GDP and real GDP, price indices for GDP and consumer spending, unemployment are projections of economic activity including GDP growth. These reports can be found on-line at: http

Johnson, Eric E.

117

Forecasting wireless communication technologies  

Science Journals Connector (OSTI)

The purpose of the paper is to present a formal comparison of a variety of multiple regression models in technology forecasting for wireless communication. We compare results obtained from multiple regression models to determine whether they provide a superior fitting and forecasting performance. Both techniques predict the year of wireless communication technology introduction from the first (1G) to fourth (4G) generations. This paper intends to identify the key parameters impacting the growth of wireless communications. The comparison of technology forecasting approaches benefits future researchers and practitioners when developing a prediction of future wireless communication technologies. The items of focus will be to understand the relationship between variable selection and model fit. Because the forecasting error was successfully reduced from previous approaches, the quadratic regression methodology is applied to the forecasting of future technology commercialisation. In this study, the data will show that the quadratic regression forecasting technique provides a better fit to the curve.

Sabrina Patino; Jisun Kim; Tugrul U. Daim

2010-01-01T23:59:59.000Z

118

Sandia National Laboratories: solar forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

119

Long-term Industrial Energy Forecasting (LIEF) model (18-sector version)  

SciTech Connect (OSTI)

The new 18-sector Long-term Industrial Energy Forecasting (LIEF) model is designed for convenient study of future industrial energy consumption, taking into account the composition of production, energy prices, and certain kinds of policy initiatives. Electricity and aggregate fossil fuels are modeled. Changes in energy intensity in each sector are driven by autonomous technological improvement (price-independent trend), the opportunity for energy-price-sensitive improvements, energy price expectations, and investment behavior. Although this decision-making framework involves more variables than the simplest econometric models, it enables direct comparison of an econometric approach with conservation supply curves from detailed engineering analysis. It also permits explicit consideration of a variety of policy approaches other than price manipulation. The model is tested in terms of historical data for nine manufacturing sectors, and parameters are determined for forecasting purposes. Relatively uniform and satisfactory parameters are obtained from this analysis. In this report, LIEF is also applied to create base-case and demand-side management scenarios to briefly illustrate modeling procedures and outputs.

Ross, M.H. [Univ. of Michigan, Ann Arbor, MI (US). Dept. of Physics; Thimmapuram, P.; Fisher, R.E.; Maciorowski, W. [Argonne National Lab., IL (US)

1993-05-01T23:59:59.000Z

120

Diagnosing Forecast Errors in Tropical Cyclone Motion  

Science Journals Connector (OSTI)

This paper reports on the development of a diagnostic approach that can be used to examine the sources of numerical model forecast error that contribute to degraded tropical cyclone (TC) motion forecasts. Tropical cyclone motion forecasts depend ...

Thomas J. Galarneau Jr.; Christopher A. Davis

2013-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Integrated Nozzle Flow, Spray, Combustion, & Emission Modeling...  

Broader source: Energy.gov (indexed) [DOE]

Spray, Combustion, & Emission Modeling using KH-ACT Primary Breakup Model & Detailed Chemistry Integrated Nozzle Flow, Spray, Combustion, & Emission Modeling using KH-ACT Primary...

122

Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs  

E-Print Network [OSTI]

Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. ...

Ganguly, Auroop Ratan

2002-01-01T23:59:59.000Z

123

Design of a next-generation regional weather research and forecast model.  

SciTech Connect (OSTI)

The Weather Research and Forecast (WRF) model is a new model development effort undertaken jointly by the National Center for Atmospheric Research (NCAR), the National Oceanic and Atmospheric Administration (NOAA), and a number of collaborating institutions and university scientists. The model is intended for use by operational NWP and university research communities, providing a common framework for idealized dynamical studies, fill physics numerical weather prediction, air-quality simulation, and regional climate. It will eventually supersede large, well-established but aging regional models now maintained by the participating institutions. The WRF effort includes re-engineering the underlying software architecture to produce a modular, flexible code designed from the outset to provide portable performance across diverse computing architectures. This paper outlines key elements of the WRF software design.

Michalakes, J.

1999-01-13T23:59:59.000Z

124

Short-Range Direct and Diffuse Irradiance Forecasts for Solar Energy Applications Based on Aerosol Chemical Transport and Numerical Weather Modeling  

Science Journals Connector (OSTI)

This study examines 2–3-day solar irradiance forecasts with respect to their application in solar energy industries, such as yield prediction for the integration of the strongly fluctuating solar energy into the electricity grid. During cloud-...

Hanne Breitkreuz; Marion Schroedter-Homscheidt; Thomas Holzer-Popp; Stefan Dech

2009-09-01T23:59:59.000Z

125

Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities  

Science Journals Connector (OSTI)

In the current uncertain context that affects both the world economy and the energy sector, with the rapid increase in the prices of oil and gas and the very unstable political situation that affects some of the largest raw materials’ producers, there is a need for developing efficient and powerful quantitative tools that allow to model and forecast fossil fuel prices, CO2 emission allowances prices as well as electricity prices. This will improve decision making for all the agents involved in energy issues. Although there are papers focused on modelling fossil fuel prices, CO2 prices and electricity prices, the literature is scarce on attempts to consider all of them together. This paper focuses on both building a multivariate model for the aforementioned prices and comparing its results with those of univariate ones, in terms of prediction accuracy (univariate and multivariate models are compared for a large span of days, all in the first 4 months in 2011) as well as extracting common features in the volatilities of the prices of all these relevant magnitudes. The common features in volatility are extracted by means of a conditionally heteroskedastic dynamic factor model which allows to solve the curse of dimensionality problem that commonly arises when estimating multivariate GARCH models. Additionally, the common volatility factors obtained are useful for improving the forecasting intervals and have a nice economical interpretation. Besides, the results obtained and methodology proposed can be useful as a starting point for risk management or portfolio optimization under uncertainty in the current context of energy markets.

Carolina García-Martos; Julio Rodríguez; María Jesús Sánchez

2013-01-01T23:59:59.000Z

126

Variational assimilation for xenon dynamical forecasts in neutronic using advanced background error covariance matrix modelling  

Science Journals Connector (OSTI)

Abstract Data assimilation method consists in combining all available pieces of information about a system to obtain optimal estimates of initial states. The different sources of information are weighted according to their accuracy by the means of error covariance matrices. Our purpose here is to evaluate the efficiency of variational data assimilation for the xenon induced oscillations forecasts in nuclear cores. In this paper we focus on the comparison between 3DVAR schemes with optimised background error covariance matrix B and a 4DVAR scheme. Tests were made in twin experiments using a simulation code which implements a mono-dimensional coupled model of xenon dynamics, thermal, and thermal–hydraulic processes. We enlighten the very good efficiency of the 4DVAR scheme as well as good results with the 3DVAR one using a careful multivariate modelling of B.

Angélique Ponçot; Jean-Philippe Argaud; Bertrand Bouriquet; Patrick Erhard; Serge Gratton; Olivier Thual

2013-01-01T23:59:59.000Z

127

A Non Parametric Model for the Forecasting of the Venezuelan Oil Prices  

E-Print Network [OSTI]

A neural net model for forecasting the prices of Venezuelan crude oil is proposed. The inputs of the neural net are selected by reference to a dynamic system model of oil prices by Mashayekhi (1995, 2001) and its performance is evaluated using two criteria: the Excess Profitability test by Anatoliev and Gerko (2005) and the characteristics of the equity curve generated by a trading strategy based on the neural net predictions. ----- Se introduce aqui un modelo no parametrico para pronosticar los precios del petroleo Venezolano cuyos insumos son seleccionados en base a un sistema dinamico que explica los precios en terminos de dichos insumos. Se describe el proceso de recoleccion y pre-procesamiento de datos y la corrida de la red y se evaluan sus pronosticos a traves de un test estadistico de predictibilidad y de las caracteristicas del Equity Curve inducido por la estrategia de compraventa bursatil generada por dichos pronosticos.

Costanzo, Sabatino; Dehne, Wafaa; Prato, Hender

2007-01-01T23:59:59.000Z

128

A Bayesian approach to forecast intermittent demand for seasonal products  

Science Journals Connector (OSTI)

This paper investigates the forecasting of a large fluctuating seasonal demand prior to peak sale season using a practical time series, collected from the US Census Bureau. Due to the extreme natural events (e.g. excessive snow fall and calamities), sales may not occur, inventory may not replenish and demand may set off unrecorded during the peak sale season. This characterises a seasonal time series to an intermittent category. A seasonal autoregressive integrated moving average (SARIMA), a multiplicative exponential smoothing (M-ES) and an effective modelling approach using Bayesian computational process are analysed in the context of seasonal and intermittent forecast. Several forecast error indicators and a cost factor are used to compare the models. In cost factor analysis, cost is measured optimally using dynamic programming model under periodic review policy. Experimental results demonstrate that Bayesian model performance is much superior to SARIMA and M-ES models, and efficient to forecast seasonal and intermittent demand.

Mohammad Anwar Rahman; Bhaba R. Sarker

2012-01-01T23:59:59.000Z

129

Effect of Observation Network Design on Meteorological Forecasts of Asian Dust Events  

Science Journals Connector (OSTI)

To improve the prediction of Asian dust events on the Korean Peninsula, meteorological fields must be accurately predicted because dust transport models require them as input. Accurate meteorological forecasts could be obtained by integrating ...

Eun-Gyeong Yang; Hyun Mee Kim; JinWoong Kim; Jun Kyung Kay

2014-12-01T23:59:59.000Z

130

Correcting and combining time series forecasters  

Science Journals Connector (OSTI)

Combined forecasters have been in the vanguard of stochastic time series modeling. In this way it has been usual to suppose that each single model generates a residual or prediction error like a white noise. However, mostly because of disturbances not ... Keywords: Artificial neural networks hybrid systems, Linear combination of forecasts, Maximum likelihood estimation, Time series forecasters, Unbiased forecasters

Paulo Renato A. Firmino; Paulo S. G. De Mattos Neto; Tiago A. E. Ferreira

2014-02-01T23:59:59.000Z

131

Leveraging Model-Based Tool Integration by Conceptual Modeling Techniques  

Science Journals Connector (OSTI)

In the context of model-based tool integration, model transformation languages are the first choice for realizing model exchange between heterogenous tools. However, the lack of a conceptual view on the integr...

Gerti Kappel; Manuel Wimmer; Werner Retschitzegger…

2011-01-01T23:59:59.000Z

132

Leveraging model-based tool integration by conceptual modeling techniques  

Science Journals Connector (OSTI)

In the context of model-based tool integration, model transformation languages are the first choice for realizing model exchange between heterogenous tools. However, the lack of a conceptual view on the integration problem and appropriate reuse mechanisms ...

Gerti Kappel; Manuel Wimmer; Werner Retschitzegger; Wieland Schwinger

2011-01-01T23:59:59.000Z

133

Forecasting the monthly volume of orders for southern pine lumber - an econometric model  

E-Print Network [OSTI]

to measure various aspects of the California redwood lumber industry. The first sought to explain the economic struc- ture of the short-run market for redwood lumber by preparing short-range forecasts of price, new orders, shipments, produc- tion, stocks... regression coefficients (20) . The second study was directed at developing a short-run forecast of new orders for redwood lumber (21) . Several forecasting techniques were developed, but econometrics, i. e. , multiple regression analysis, provided...

Jackson, Ben Douglas

2012-06-07T23:59:59.000Z

134

Study and implementation of mesoscale weather forecasting models in the wind industry.  

E-Print Network [OSTI]

?? As the wind industry is developing, it is asking for more reliable short-term wind forecasts to better manage the wind farms’ operations and electricity… (more)

Jourdier, Bénédicte

2012-01-01T23:59:59.000Z

135

A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting  

E-Print Network [OSTI]

is critical for coastal California solar forecasting.   affecting solar irradiance in southern California.   solar  photovoltaic generation (the southern California 

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

136

Holt’s exponential smoothing and neural network models for forecasting interval-valued time series  

Science Journals Connector (OSTI)

Interval-valued time series are interval-valued data that are collected in a chronological sequence over time. This paper introduces three approaches to forecasting interval-valued time series. The first two approaches are based on multilayer perceptron (MLP) neural networks and Holt’s exponential smoothing methods, respectively. In Holt’s method for interval-valued time series, the smoothing parameters are estimated by using techniques for non-linear optimization problems with bound constraints. The third approach is based on a hybrid methodology that combines the MLP and Holt models. The practicality of the methods is demonstrated through simulation studies and applications using real interval-valued stock market time series.

André Luis Santiago Maia; Francisco de A.T. de Carvalho

2011-01-01T23:59:59.000Z

137

Forecasting a large number of tropical cyclone intensities around Japan using a high-resolution atmosphere-ocean coupled model  

Science Journals Connector (OSTI)

This work quantifies the benefits of using a high-resolution atmosphere-ocean coupled model in the tropical cyclone (TC) intensity forecasts in the vicinity of Japan. To do so, a large number of high-resolution calculations were performed by ...

Kosuke Ito; Tohru Kuroda; Kazuo Saito; Akiyoshi Wada

138

Inverse modeling and forecasting for the exploitation of the Pauzhetsky geothermal field, Kamchatka, Russia  

SciTech Connect (OSTI)

A three-dimensional numerical model of the Pauzhetsky geothermal field has been developed based on a conceptual hydrogeological model of the system. It extends over a 13.6-km2 area and includes three layers: (1) a base layer with inflow; (2) a geothermal reservoir; and (3) an upper layer with discharge and recharge/infiltration areas. Using the computer program iTOUGH2 (Finsterle, 2004), the model is calibrated to a total of 13,675 calibration points, combining natural-state and 1960-2006 exploitation data. The principal model parameters identified and estimated by inverse modeling include the fracture permeability and fracture porosity of the geothermal reservoir, the initial natural upflow rate, the base-layer porosity, and the permeabilities of the infiltration zones. Heat and mass balances derived from the calibrated model helped identify the sources of the geothermal reserves in the field. With the addition of five makeup wells, simulation forecasts for the 2007-2032 period predict a sustainable average steam production of 29 kg/s, which is sufficient to maintain the generation of 6.8 MWe at the Pauzhetsky power plant.

Finsterle, Stefan; Kiryukhin, A.V.; Asaulova, N.P.; Finsterle, S.

2008-04-01T23:59:59.000Z

139

Incorporation of 3D Shortwave Radiative Effects within the Weather Research and Forecasting Model  

SciTech Connect (OSTI)

A principal goal of the Atmospheric Radiation Measurement (ARM) Program is to understand the 3D cloud-radiation problem from scales ranging from the local to the size of global climate model (GCM) grid squares. For climate models using typical cloud overlap schemes, 3D radiative effects are minimal for all but the most complicated cloud fields. However, with the introduction of ''superparameterization'' methods, where sub-grid cloud processes are accounted for by embedding high resolution 2D cloud system resolving models within a GCM grid cell, the impact of 3D radiative effects on the local scale becomes increasingly relevant (Randall et al. 2003). In a recent study, we examined this issue by comparing the heating rates produced from a 3D and 1D shortwave radiative transfer model for a variety of radar derived cloud fields (O'Hirok and Gautier 2005). As demonstrated in Figure 1, the heating rate differences for a large convective field can be significant where 3D effects produce areas o f intense local heating. This finding, however, does not address the more important question of whether 3D radiative effects can alter the dynamics and structure of a cloud field. To investigate that issue we have incorporated a 3D radiative transfer algorithm into the Weather Research and Forecasting (WRF) model. Here, we present very preliminary findings of a comparison between cloud fields generated from a high resolution non-hydrostatic mesoscale numerical weather model using 1D and 3D radiative transfer codes.

O'Hirok, W.; Ricchiazzi, P.; Gautier, C.

2005-03-18T23:59:59.000Z

140

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sánchez The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors,

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect (OSTI)

The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-07-01T23:59:59.000Z

142

Integrated Hydrogen Storage System Model  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

WSRC-TR-2007-00440, REVISION 0 WSRC-TR-2007-00440, REVISION 0 Keywords: Hydrogen Kinetics, Hydrogen Storage Vessel Metal Hydride Retention: Permanent Integrated Hydrogen Storage System Model Bruce J. Hardy November 16, 2007 Washington Savannah River Company Savannah River Site Aiken, SC 29808 Prepared for the U.S. Department of Energy Under Contract Number DEAC09-96-SR18500 DISCLAIMER This report was prepared for the United States Department of Energy under Contract No. DE-AC09-96SR18500 and is an account of work performed under that contract. Neither the United States Department of Energy, nor WSRC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for accuracy, completeness, or usefulness, of any information,

143

NREL: Technology Deployment - Integrated Deployment Model  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Integrated Deployment Model Integrated Deployment Model NREL's integrated deployment model provides a framework to focus on the national goal of accelerating market adoption of clean energy technologies through local efforts. With support from the U.S. Department of Energy (DOE), NREL developed and applies the integrated deployment model to select projects including disaster recovery, statewide activities, federal agency support, island activities, and community renewable energy deployment. How the Model Works To address the complex challenges of multi-technology, multi-stakeholder, and multi-fuel deployment, NREL created the integrated deployment model to support each technology area separately but also consider the integration points between the technologies. NREL also identifies the cross-cutting

144

The Los Alamos dynamic radiation environment assimilation model (DREAM) for space weather specification and forecasting  

SciTech Connect (OSTI)

The Dynamic Radiation Environment Assimilation Model (DREAM) was developed at Los Alamos National Laboratory to assess, quantify, and predict the hazards from the natural space environment and the anthropogenic environment produced by high altitude nuclear explosions (HANE). DREAM was initially developed as a basic research activity to understand and predict the dynamics of the Earth's Van Allen radiation belts. It uses Kalman filter techniques to assimilate data from space environment instruments with a physics-based model of the radiation belts. DREAM can assimilate data from a variety of types of instruments and data with various levels of resolution and fidelity by assigning appropriate uncertainties to the observations. Data from any spacecraft orbit can be assimilated but DREAM was designed to function with as few as two spacecraft inputs: one from geosynchronous orbit and one from GPS orbit. With those inputs, DREAM can be used to predict the environment at any satellite in any orbit whether space environment data are available in those orbits or not. Even with very limited data input and relatively simple physics models, DREAM specifies the space environment in the radiation belts to a high level of accuracy. DREAM has been extensively tested and evaluated as we transition from research to operations. We report here on one set of test results in which we predict the environment in a highly-elliptical polar orbit. We also discuss long-duration reanalysis for spacecraft design, using DREAM for real-time operations, and prospects for 1-week forecasts of the radiation belt environment.

Reeves, Geoffrey D [Los Alamos National Laboratory; Friedel, Reiner H W [Los Alamos National Laboratory; Chen, Yue [Los Alamos National Laboratory; Koller, Josef [Los Alamos National Laboratory; Henderson, Michael G [Los Alamos National Laboratory

2008-01-01T23:59:59.000Z

145

Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting  

Science Journals Connector (OSTI)

Because poor visibility conditions have a considerable influence on airport traffic, a need exists for accurate and updated fog and low-cloud forecasts. Couche Brouillard Eau Liquide (COBEL)-Interactions between Soil, Biosphere, and Atmosphere (...

Samuel Rémy; Thierry Bergot

2010-05-01T23:59:59.000Z

146

A Transaction Choice Model for Forecasting Demand for Alternative-Fuel Vehicles  

E-Print Network [OSTI]

Forecasting Demand Alternative-Fuel Vehicles for DavldNG DEMANDFOR ALTERNATIVE-FUEL VEHICLES DavidBrownstone,interested in promoting alternative-fuel vehicles. Tl’us is

Brownstone, David; Bunch, David S.; Golob, Thomas F.; Ren, Weiping

1996-01-01T23:59:59.000Z

147

A Transactions Choice Model for Forecasting Demand for Alternative-Fuel Vehicles  

E-Print Network [OSTI]

Forecasting Demand Alternative-Fuel Vehicles for DavldNG DEMANDFOR ALTERNATIVE-FUEL VEHICLES DavidBrownstone,interested in promoting alternative-fuel vehicles. Tl’us is

Brownstone, David; Bunch, David S; Golob, Thomas F; Ren, Weiping

1996-01-01T23:59:59.000Z

148

A Data Model for Data Integration  

Science Journals Connector (OSTI)

Data integration systems provide a uniform query interface (UQI) to multiple, autonomous data sources [Alon Y. Halevy. Answering queries using views: A survey. The VLDB Journal, 10(4):270-294, 2001]. This paper presents the universal data model (UDM) ... Keywords: Data Integration, Data Model, Query Languages

James J. Lu

2006-03-01T23:59:59.000Z

149

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sanchez by Esmeralda Sanchez Errata -(7/14/04) The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors, expressed as the percentage difference between the Reference Case projection and actual historic value, shown for every AEO and for each year in the forecast horizon (for a given variable). The historical data are typically taken from the Annual Energy Review (AER). The last column of Table 1 provides a summary of the most recent average absolute forecast errors. The calculation of the forecast error is shown in more detail in Tables 2 through 18. Because data for coal prices to electric generating plants were not available from the AER, data from the Monthly Energy Review (MER), July 2003 were used.

150

Energy demand forecasting: industry practices and challenges  

Science Journals Connector (OSTI)

Accurate forecasting of energy demand plays a key role for utility companies, network operators, producers and suppliers of energy. Demand forecasts are utilized for unit commitment, market bidding, network operation and maintenance, integration of renewable ... Keywords: analytics, energy demand forecasting, machine learning, renewable energy sources, smart grids, smart meters

Mathieu Sinn

2014-06-01T23:59:59.000Z

151

Forecasting the daily outbreak of topic-level political risk from social media using hidden Markov model-based techniques  

Science Journals Connector (OSTI)

Abstract Nowadays, as an arena of politics, social media ignites political protests, so analyzing topics discussed negatively in the social media has increased in importance for detecting a nation's political risk. In this context, this paper designs and examines an automatic approach to forecast the daily outbreak of political risk from social media at a topic level. It evaluates the forecasting performances of topic features, investigated among the previous works that analyze social media data for politics, hidden Markov model (HMM)-based techniques, widely used for the anomaly detection with time-series data, and detection models, into which the topic features and the detection techniques are combined. When applied to South Korea's Web forum, Daum Agora, statistical comparisons with the constraints of false positive rate of political risk, and eventually the predictive governance benefits the people.

Jong Hwan Suh

2014-01-01T23:59:59.000Z

152

INTEGRATED FISCHER TROPSCH MODULAR PROCESS MODEL  

SciTech Connect (OSTI)

With declining petroleum reserves, increased world demand, and unstable politics in some of the world’s richest oil producing regions, the capability for the U.S. to produce synthetic liquid fuels from domestic resources is critical to national security and economic stability. Coal, biomass and other carbonaceous materials can be converted to liquid fuels using several conversion processes. The leading candidate for large-scale conversion of coal to liquid fuels is the Fischer Tropsch (FT) process. Process configuration, component selection, and performance are interrelated and dependent on feed characteristics. This paper outlines a flexible modular approach to model an integrated FT process that utilizes a library of key component models, supporting kinetic data and materials and transport properties allowing rapid development of custom integrated plant models. The modular construction will permit rapid assessment of alternative designs and feed stocks. The modeling approach consists of three thrust areas, or “strands” – model/module development, integration of the model elements into an end to end integrated system model, and utilization of the model for plant design. Strand 1, model/module development, entails identifying, developing, and assembling a library of codes, user blocks, and data for FT process unit operations for a custom feedstock and plant description. Strand 2, integration development, provides the framework for linking these component and subsystem models to form an integrated FT plant simulation. Strand 3, plant design, includes testing and validation of the comprehensive model and performing design evaluation analyses.

Donna Post Guillen; Richard Boardman; Anastasia M. Gribik; Rick A. Wood; Robert A. Carrington

2007-12-01T23:59:59.000Z

153

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation by Susan H. Holte In this paper, the Office of Integrated Analysis and Forecasting (OIAF) of the Energy Information Administration (EIA) evaluates the projections published in the Annual Energy Outlook (AEO), (1) by comparing the projections from the Annual Energy Outlook 1982 through the Annual Energy Outlook 2001 with actual historical values. A set of major consumption, production, net import, price, economic, and carbon dioxide emissions variables are included in the evaluation, updating similar papers from previous years. These evaluations also present the reasons and rationales for significant differences. The Office of Integrated Analysis and Forecasting has been providing an

154

Improving an Accuracy of ANN-Based Mesoscale-Microscale Coupling Model by Data Categorization: With Application to Wind Forecast for Offshore and Complex Terrain Onshore Wind Farms  

Science Journals Connector (OSTI)

The ANN-based mesoscale-microscale coupling model forecasts wind speed and wind direction with high accuracy for wind parks located in complex terrain onshore, yet some weather regimes remains unresolved and f...

Alla Sapronova; Catherine Meissner…

2014-01-01T23:59:59.000Z

155

Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model  

Science Journals Connector (OSTI)

Abstract Electricity consumption forecasting has been always playing a vital role in power system management and planning. Inaccurate prediction may cause wastes of scarce energy resource or electricity shortages. However, forecasting electricity consumption has proven to be a challenging task due to various unstable factors. Especially, China is undergoing a period of economic transition, which highlights this difficulty. This paper proposes a time-varying-weight combining method, i.e. High-order Markov chain based Time-varying Weighted Average (HM-TWA) method to predict the monthly electricity consumption in China. HM-TWA first calculates the in-sample time-varying combining weights by quadratic programming for the individual forecasts. Then it predicts the out-of-sample time-varying adaptive weights through extrapolating these in-sample weights using a high-order Markov chain model. Finally, the combined forecasts can be obtained. In addition, to ensure that the sample data have the same properties as the required forecasts, a reasonable multi-step-ahead forecasting scheme is designed for HM-TWA. The out-of-sample forecasting performance evaluation shows that HM-TWA outperforms the component models and traditional combining methods, and its effectiveness is further verified by comparing it with some other existing models.

Weigang Zhao; Jianzhou Wang; Haiyan Lu

2014-01-01T23:59:59.000Z

156

NREL: Vehicle Ancillary Loads Reduction - Integrated Modeling  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Integrated Modeling Integrated Modeling NREL's Vehicle Ancillary Loads Reduction (VALR) team predicts the impact of advanced vehicle cooling technologies before testing by using an integrated modeling process. Evaluating the heat load on a vehicle under real world conditions is a difficult task. An accepted method to evaluate passenger compartment airflow and heat transfer is computational fluid dynamics. (CFD). Combining analytical models with CFD provides a powerful tool to assist industry both on current vehicles and on future design studies. Flow chart showing the vehicle integrated modeling process which considers solar radiation, air conditioning, and vehicles with CAD, glazing, cabin thermal/fluid, and thermal comfort modeling tools. Results are provided for fuel economy, tailpipe emissions and occupant thermal comfort.

157

Perspectives of Integrated Modeling at NERSC  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

on Integrated Whole-Device Modeling on Integrated Whole-Device Modeling at NERSC Alexei Y. Pankin 1 , Arnold H. Kritz 2 , and Tariq Rafiq 2 1 Tech-X Corporation, Boulder, CO 2 Lehigh University, Bethlehem, PA Integrated Whole-Device Modeling of Tokamak Plasmas Studies in isolation of elements that describe plasma behavior (plasma heating, MHD equilibria, large scale instabilities, core and edge transport ...) * Do not capture interactive nature of physics described in whole-device integrated modeling simulations  It is important that we understand effects that result from interactions between various physical processes in tokamak plasmas Predictive whole-device modeling helps avoid costly design mistakes * Facilitates the optimization and control of experimental scenarios in order to make the most effective use of expensive experiments

158

Forecasting GHG emissions using an optimized artificial neural network model based on correlation and principal component analysis  

Science Journals Connector (OSTI)

Abstract The prediction of GHG emissions is very important due to their negative impacts on climate and global warming. The aim of this study was to develop a model for GHG forecasting emissions at the national level using a new approach based on artificial neural networks (ANN) and broadly available sustainability, economical and industrial indicators acting as inputs. The ANN model architecture and training parameters were optimized, with inputs being selected using correlation analysis and principal component analysis. The developed ANN models were compared with the corresponding multiple linear regression (MLR) model, while an ANN model created using transformed inputs (principal components) was compared with a principal component regression (PCR) model. Since the best results were obtained with the ANN model based on correlation analysis, that particular model was selected for the actual 2011 GHG emissions forecasting. The relative errors of the 2010 GHG emissions predictions were used to adjust the ANN model predictions for 2011, which subsequently resulted in the adjusted 2011 predictions having a MAPE value of only 3.60%. Sensitivity analysis showed that gross inland energy consumption had the highest sensitivity to GHG emissions.

Davor Z. Antanasijevi?; Mirjana ?. Risti?; Aleksandra A. Peri?-Gruji?; Viktor V. Pocajt

2014-01-01T23:59:59.000Z

159

CIMS: An Integrated US-Canadian Model  

E-Print Network [OSTI]

CIMS: An Integrated US-Canadian Model John Nyboer, Simon Fraser University As the US addresses energy supply security and, at a state level, various environmental objectives, it is not clear what effect these will have on Canada's exports... CIMS: An Integrated US-Canadian Model John Nyboer, Simon Fraser University As the US addresses energy supply security and, at a state level, various environmental objectives, it is not clear what effect these will have on Canada's exports...

Nyboer, J.

2006-01-01T23:59:59.000Z

160

Integration of EBS Models with Generic Disposal System Models | Department  

Broader source: Energy.gov (indexed) [DOE]

Integration of EBS Models with Generic Disposal System Models Integration of EBS Models with Generic Disposal System Models Integration of EBS Models with Generic Disposal System Models This report summarizes research activities on engineered barrier system (EBS) model integration with the generic disposal system model (GDSM), and used fuel degradation and radionuclide mobilization (RM) in support of the EBS evaluation and tool development within the Used Fuel Disposition campaign. This report addresses: predictive model capability for used nuclear fuel degradation based on electrochemical and thermodynamic principles, radiolysis model to evaluate the U(VI)-H2O-CO2 system, steps towards the evaluation of uranium alteration products, discussion of instant release fraction (IRF) of radionuclides from the nuclear fuel, and

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Integration of EBS Models with Generic Disposal System Models | Department  

Broader source: Energy.gov (indexed) [DOE]

Integration of EBS Models with Generic Disposal System Models Integration of EBS Models with Generic Disposal System Models Integration of EBS Models with Generic Disposal System Models This report summarizes research activities on engineered barrier system (EBS) model integration with the generic disposal system model (GDSM), and used fuel degradation and radionuclide mobilization (RM) in support of the EBS evaluation and tool development within the Used Fuel Disposition campaign. This report addresses: predictive model capability for used nuclear fuel degradation based on electrochemical and thermodynamic principles, radiolysis model to evaluate the U(VI)-H2O-CO2 system, steps towards the evaluation of uranium alteration products, discussion of instant release fraction (IRF) of radionuclides from the nuclear fuel, and

162

Every cloud has a silver lining: Weather forecasting models could predict brain tumor  

E-Print Network [OSTI]

, and combine them with incoming data streams from weather stations and satellites. Now, an innovative new study methodology used to assimilate data for weather forecasting could be used to predict the spread of brain. Synthetic magnetic resonance images of a hypothetical tumor were used for this purpose. Data assimilation

Kuang, Yang

163

Results of the Regional Earthquake Likelihood Models (RELM) test of earthquake forecasts in California  

Science Journals Connector (OSTI)

...given in Table 1, as well as background earthquakes...in the test region as well as forecasts that excluded...about 50 km south of the Mexico–United States border...this is the Cerra Prieto geothermal area...earthquake in northern Mexico. This earthquake occurred...

Ya-Ting Lee; Donald L. Turcotte; James R. Holliday; Michael K. Sachs; John B. Rundle; Chien-Chih Chen; Kristy F. Tiampo

2011-01-01T23:59:59.000Z

164

Model error in weather forecasting D. Orrell 1,2 , L. Smith 1,3 , J. Barkmeijer 4 , and T. Palmer 4  

E-Print Network [OSTI]

numerical weather prediction mod­ els. A simple law is derived to relate model error to likely shadowingModel error in weather forecasting D. Orrell 1,2 , L. Smith 1,3 , J. Barkmeijer 4 , and T. Palmer 4 in the model, and inac­ curate initial conditions (Bjerknes, 1911). Because weather models are thought

Smith, Leonard A

165

BMA Probabilistic Quantitative Precipitation Forecasting over the Huaihe Basin Using TIGGE Multimodel Ensemble Forecasts  

Science Journals Connector (OSTI)

Bayesian model averaging (BMA) probability quantitative precipitation forecast (PQPF) models were established by calibrating their parameters using 1–7-day ensemble forecasts of 24-h accumulated precipitation, and observations from 43 ...

Jianguo Liu; Zhenghui Xie

2014-04-01T23:59:59.000Z

166

ON THE IMPACT OF SUPER RESOLUTION WSR-88D DOPPLER RADAR DATA ASSIMILATION ON HIGH RESOLUTION NUMERICAL MODEL FORECASTS  

SciTech Connect (OSTI)

Assimilation of radar velocity and precipitation fields into high-resolution model simulations can improve precipitation forecasts with decreased 'spin-up' time and improve short-term simulation of boundary layer winds (Benjamin, 2004 & 2007; Xiao, 2008) which is critical to improving plume transport forecasts. Accurate description of wind and turbulence fields is essential to useful atmospheric transport and dispersion results, and any improvement in the accuracy of these fields will make consequence assessment more valuable during both routine operation as well as potential emergency situations. During 2008, the United States National Weather Service (NWS) radars implemented a significant upgrade which increased the real-time level II data resolution to 8 times their previous 'legacy' resolution, from 1 km range gate and 1.0 degree azimuthal resolution to 'super resolution' 250 m range gate and 0.5 degree azimuthal resolution (Fig 1). These radar observations provide reflectivity, velocity and returned power spectra measurements at a range of up to 300 km (460 km for reflectivity) at a frequency of 4-5 minutes and yield up to 13.5 million point observations per level in super-resolution mode. The migration of National Weather Service (NWS) WSR-88D radars to super resolution is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current operational mesoscale model domains utilize grid spacing several times larger than the legacy data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of super resolution reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution is investigated here to determine the impact of the improved data resolution on model predictions.

Chiswell, S

2009-01-11T23:59:59.000Z

167

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

J.B. , 2004: Probabilistic wind power forecasts using localforecast intervals for wind power output using NWP-predictedsources such as wind and solar power. Integration of this

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

168

Modeling for System Integration Studies (Presentation)  

SciTech Connect (OSTI)

This presentation describes some the data requirements needed for grid integration modeling and provides real-world examples of such data and its format. Renewable energy integration studies evaluate the operational impacts of variable generation. Transmission planning studies investigate where new transmission is needed to transfer energy from generation sources to load centers. Both use time-synchronized wind and solar energy production and load as inputs. Both examine high renewable energy penetration scenarios in the future.

Orwig, K. D.

2012-05-01T23:59:59.000Z

169

A soil moisture assimilation scheme using satellite-retrieved skin temperature in meso-scale weather forecast model  

Science Journals Connector (OSTI)

A thermodynamically consistent soil moisture assimilation scheme for clear sky and snow free conditions has been developed for the meso-scale modeling system in the Arctic region by using satellite-derived skin temperatures. Parallel control and sensitivity modeling experiments were designed and their results demonstrated that the assimilation scheme successfully improves the soil moistures that were deliberately perturbed initially, indicating capability of the scheme to correct bias in the soil moisture initialization. Moreover, the resultant benefit of this assimilation scheme does not only lie in the improvement of soil moisture; the skin temperature also consequently exhibits improvements in a thermodynamic consistency. A real application of the assimilation scheme with satellite-retrieved skin temperature exhibited noticeable positive impacts on the modeling simulation and weather forecast; the model obviously captured meso-scale features of soil moistures as well as the skin temperatures. The warming tendency bias in original model simulations was removed to a considerable extent by this assimilation scheme.

Jing Zhang; Xiangdong Zhang

2010-01-01T23:59:59.000Z

170

A comparison between a hydro-wind plant and wind speed forecasting using ARIMA models  

Science Journals Connector (OSTI)

In this paper we will present a comparison between two options for harnessing wind power. We will first analyze the behaviour of a wind farm that goes to the electricity market having previously made a forecast of wind speed while accepting the deviation penalties that these may incur. Second we will study the possibility of the wind farm not going to the market individually but as part of a hydro-wind plant.

2014-01-01T23:59:59.000Z

171

CTBT integrated verification system evaluation model supplement  

SciTech Connect (OSTI)

Sandia National Laboratories has developed a computer based model called IVSEM (Integrated Verification System Evaluation Model) to estimate the performance of a nuclear detonation monitoring system. The IVSEM project was initiated in June 1994, by Sandia's Monitoring Systems and Technology Center and has been funded by the U.S. Department of Energy's Office of Nonproliferation and National Security (DOE/NN). IVSEM is a simple, ''top-level,'' modeling tool which estimates the performance of a Comprehensive Nuclear Test Ban Treaty (CTBT) monitoring system and can help explore the impact of various sensor system concepts and technology advancements on CTBT monitoring. One of IVSEM's unique features is that it integrates results from the various CTBT sensor technologies (seismic, in sound, radionuclide, and hydroacoustic) and allows the user to investigate synergy among the technologies. Specifically, IVSEM estimates the detection effectiveness (probability of detection), location accuracy, and identification capability of the integrated system and of each technology subsystem individually. The model attempts to accurately estimate the monitoring system's performance at medium interfaces (air-land, air-water) and for some evasive testing methods such as seismic decoupling. The original IVSEM report, CTBT Integrated Verification System Evaluation Model, SAND97-25 18, described version 1.2 of IVSEM. This report describes the changes made to IVSEM version 1.2 and the addition of identification capability estimates that have been incorporated into IVSEM version 2.0.

EDENBURN,MICHAEL W.; BUNTING,MARCUS; PAYNE JR.,ARTHUR C.; TROST,LAWRENCE C.

2000-03-02T23:59:59.000Z

172

Operational Rainfall and Flow Forecasting for the Panama Canal Watershed  

Science Journals Connector (OSTI)

An integrated hydrometeorological system was designed for the utilization of data from various sensors in the 3300 km2 Panama Canal Watershed for the purpose of producing ... forecasts. These forecasts are used b...

Konstantine P. Georgakakos; Jason A. Sperfslage

2005-01-01T23:59:59.000Z

173

Investigation of model parameters for high-resolution wind energy forecasting: Case studies over simple and complex terrain  

Science Journals Connector (OSTI)

Abstract Wind power forecasting, turbine micrositing, and turbine design require high-resolution simulations of atmospheric flow. Case studies at two West Coast North American wind farms, one with simple and one with complex terrain, are explored using the Weather Research and Forecasting (WRF) model. Both synoptically and locally driven events that include some ramping are considered. The performance of the model with different grid nesting configurations, turbulence closures, and grid resolutions is investigated through comparisons with observation data. For the simple terrain site, no significant improvement in the simulation results is found when using higher resolution. In contrast, for the complex terrain site, there is significant improvement when using higher resolution, but only during the locally driven event. This suggests the possibility that computational resources could be spared under certain conditions, for example when the topography is adequately resolved at coarser resolutions. Physical parameters such as soil moisture have a very large effect, but mostly for the locally forced events for both simple and complex terrain. The effect of the PBL scheme choice varies significantly depending on the meteorological forcing and terrain. On average, prognostic TKE equation schemes perform better than non-local eddy viscosity schemes.

Nikola Marjanovic; Sonia Wharton; Fotini K. Chow

2014-01-01T23:59:59.000Z

174

Need for an Integrated Risk Model  

Broader source: Energy.gov (indexed) [DOE]

Need for An Integrated Risk Need for An Integrated Risk Model Michael Salmon, LANL Voice: 505-665-7244 Fax: 505-665-2897 salmon@lanl.gov 10/22/2008 p. 2, LA-UR 11-06023 Purpose * To highlight some observations on safety strategy when concerned with NPH * To encourage discussion and collaboration on the use of an integrated risk model at sites * To propose a test case for use of a sample case 10/22/2008 p. 3, LA-UR 11-06023 Observations * SAFER Comments of Peer Reviewers - There is a need to consider operator interaction - What about fire following earthquake? - What about flood following earthquake? - lessons from kashiwazake * Sites do not consider common cause initiating events * Investment decisions are not based on quantitative estimates of risk reduction 10/22/2008 p. 4, LA-UR 11-06023

175

Tracking tropical cloud systems - Observations for the diagnosis of simulations by the Weather Research and Forecasting (WRF) Model  

SciTech Connect (OSTI)

To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the vicinity of the ARM Tropical Western Pacific sites. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest a computational paradox where, even though the size of the simulated systems are about half of that observed, their longevities are still similar. The explanation for this seeming incongruity will be explored.

Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E.; Jensen, M.; Zhang, M.

2010-03-15T23:59:59.000Z

176

Tracking tropical cloud systems for the diagnosis of simulations by the weather research and forecasting (WRF) model  

SciTech Connect (OSTI)

To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the tropical warm pool. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, J. Geophys. Res., 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest that the organization of the mesoscale convective systems is particularly sensitive to the cloud microphysics parameterization used.

Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E. P.; Jensen, M. P.; Zhang, M. H.; Boer, E.

2010-06-27T23:59:59.000Z

177

Integrated Modeling for Intelligent Battery Thermal Management  

Science Journals Connector (OSTI)

Effective thermal management is crucial to the optimal operation of lithium ion batteries and its health management. However, the thermal behaviors of batteries are governed by complex chemical process whose parameters will degrade over time and different ... Keywords: integrated modeling, distributed parameter system, battery thermal management, intelligent learning

Zhen Liu; Han-Xiong Li

2013-10-01T23:59:59.000Z

178

Calibrated Precipitation Forecasts for a Limited-Area Ensemble Forecast System Using Reforecasts  

Science Journals Connector (OSTI)

The calibration of numerical weather forecasts using reforecasts has been shown to increase the skill of weather predictions. Here, the precipitation forecasts from the Consortium for Small Scale Modeling Limited Area Ensemble Prediction System (...

Felix Fundel; Andre Walser; Mark A. Liniger; Christoph Frei; Christof Appenzeller

2010-01-01T23:59:59.000Z

179

NREL: Transmission Grid Integration - FESTIV Model  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

FESTIV Model FESTIV Model The Flexible Energy Scheduling Tool for Integration of Variable Generation (FESTIV) is a model that simulates the behavior of the electric power system to help researchers understand the impacts of variability and uncertainty on operating reserves requirements. FESTIV includes security-constrained unit commitment, security-constrained economic dispatch, and automatic generation control sub-models. Electric power system operators use a variety of scheduling techniques to match electricity generation and demand. When the total supply of energy is different from the total demand, system operators must deploy operating reserves (including regulating, following, contingency, and ramping reserves) to correct the energy imbalance. The way they do this and,

180

Weather Research and Forecasting prevision model as a tool to search for the best sites for astronomy: application to La Palma, Canary Islands  

Science Journals Connector (OSTI)

......the capability of WRF to predict the...Palma. Maps of the wind velocity, cloudiness...the use of the WRF model in an astronomical...launched on our local computer every...at 0600-ut (local time is equal to...C_N^2$ The WRF model gives vertical...temperature and the wind velocity forecast......

C. Giordano; J. Vernin; H. Trinquet; C. Muñoz-Tuñón

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Forecast Prices  

Gasoline and Diesel Fuel Update (EIA)

Notes: Notes: Prices have already recovered from the spike, but are expected to remain elevated over year-ago levels because of the higher crude oil prices. There is a lot of uncertainty in the market as to where crude oil prices will be next winter, but our current forecast has them declining about $2.50 per barrel (6 cents per gallon) from today's levels by next October. U.S. average residential heating oil prices peaked at almost $1.50 as a result of the problems in the Northeast this past winter. The current forecast has them peaking at $1.08 next winter, but we will be revisiting the outlook in more detail next fall and presenting our findings at the annual Winter Fuels Conference. Similarly, diesel prices are also expected to fall. The current outlook projects retail diesel prices dropping about 14 cents per gallon

182

CTBT Integrated Verification System Evaluation Model  

SciTech Connect (OSTI)

Sandia National Laboratories has developed a computer based model called IVSEM (Integrated Verification System Evaluation Model) to estimate the performance of a nuclear detonation monitoring system. The IVSEM project was initiated in June 1994, by Sandia`s Monitoring Systems and Technology Center and has been funded by the US Department of Energy`s Office of Nonproliferation and National Security (DOE/NN). IVSEM is a simple, top-level, modeling tool which estimates the performance of a Comprehensive Nuclear Test Ban Treaty (CTBT) monitoring system and can help explore the impact of various sensor system concepts and technology advancements on CTBT monitoring. One of IVSEM`s unique features is that it integrates results from the various CTBT sensor technologies (seismic, infrasound, radionuclide, and hydroacoustic) and allows the user to investigate synergy among the technologies. Specifically, IVSEM estimates the detection effectiveness (probability of detection) and location accuracy of the integrated system and of each technology subsystem individually. The model attempts to accurately estimate the monitoring system`s performance at medium interfaces (air-land, air-water) and for some evasive testing methods such as seismic decoupling. This report describes version 1.2 of IVSEM.

Edenburn, M.W.; Bunting, M.L.; Payne, A.C. Jr.

1997-10-01T23:59:59.000Z

183

Waste Form Degradation Model Integration for Engineered Materials Performance  

Broader source: Energy.gov [DOE]

The collaborative approach to the glass and metallic waste form degradation modeling activities includes process model development (including first-principles approaches) and model integration—both...

184

An assessment of electrical load forecasting using artificial neural network  

Science Journals Connector (OSTI)

The forecasting of electricity demand has become one of the major research fields in electrical engineering. The supply industry requires forecasts with lead times, which range from the short term (a few minutes, hours, or days ahead) to the long term (up to 20 years ahead). The major priority for an electrical power utility is to provide uninterrupted power supply to its customers. Long term peak load forecasting plays an important role in electrical power systems in terms of policy planning and budget allocation. This paper presents a peak load forecasting model using artificial neural networks (ANN). The approach in the paper is based on multi-layered back-propagation feed forward neural network. For annual forecasts, there should be 10 to 12 years of historical monthly data available for each electrical system or electrical buss. A case study is performed by using the proposed method of peak load data of a state electricity board of India which maintain high quality, reliable, historical data providing the best possible results. Model's quality is directly dependent upon data integrity.

V. Shrivastava; R.B. Misra; R.C. Bansal

2012-01-01T23:59:59.000Z

185

Plant design: Integrating Plant and Equipment Models  

SciTech Connect (OSTI)

Like power plant engineers, process plant engineers must design generating units to operate efficiently, cleanly, and profitably despite fluctuating costs for raw materials and fuels. To do so, they increasingly create virtual plants to enable evaluation of design concepts without the expense of building pilot-scale or demonstration facilities. Existing computational models describe an entire plant either as a network of simplified equipment models or as a single, very detailed equipment model. The Advanced Process Engineering Co-Simulator (APECS) project (Figure 5) sponsored by the U.S. Department of Energy's National Energy Technology Laboratory (NETL) seeks to bridge the gap between models by integrating plant modeling and equipment modeling software. The goal of the effort is to provide greater insight into the performance of proposed plant designs. The software integration was done using the process-industry standard CAPE-OPEN (Computer Aided Process Engineering–Open), or CO interface. Several demonstration cases based on operating power plants confirm the viability of this co-simulation approach.

Sloan, David (Alstrom Power); Fiveland, Woody (Alstrom Power); Zitney, S.E.; Osawe, Maxwell (Ansys, Inc.)

2007-08-01T23:59:59.000Z

186

Generalized parafermionic theory and integrable lattice models  

Science Journals Connector (OSTI)

We show that the criticality of integrable lattice models based on the Lie algebras An,Dn,En can be understood as the product of certain numbers of bosonic fields and a generalized parafermionic (fractional spin) theory (GPT). We compute the central charge of the GPT using the thermodynamic Bethe-ansatz approach. For the model associated with the A2 Lie algebra, we propose that the associated GPT can be described by a composition of Ising and tricritical-Ising conformal field theories.

Márcio José Martins

1990-10-22T23:59:59.000Z

187

ZHANG, XUEJIN. Adapting the Weather Research and Forecasting Model for the Simulation of Regional Climate in East Africa. (Under the direction of Dr. Lian Xie).  

E-Print Network [OSTI]

and society for regional climate information. The current Weather Research and Forecasting (WRF) RCM inherits several advantages of the original WRF model. For example, (1) it can be used for multiple scale infrastructure to distinguish the scientific problems from engineering problems. In order to adapt WRF for long

Liu, Paul

188

A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting  

E-Print Network [OSTI]

Multiscale Numerical Weather Prediction Model.   Progress assimilating numerical weather prediction model for solar customizable  numerical weather prediction model that is 

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

189

DOD/NREL Model Integrates Vehicles, Renewables & Microgrid (Fact Sheet)  

SciTech Connect (OSTI)

Fact sheet on microgrid model created by the Electric Vehicle Grid Integration program at the Fort Carson Army facility.

Not Available

2011-02-01T23:59:59.000Z

190

Advanced chemistry-transport modeling and observing systems allow daily air quality observations, short-term forecasts, and real-time analyses of air quality at the global and  

E-Print Network [OSTI]

Advanced chemistry-transport modeling and observing systems allow daily air quality observations, short-term forecasts, and real-time analyses of air quality at the global and European scales control measures that could be taken for managing such episodes, European-scale air quality forecasting

Paris-Sud XI, Université de

191

Towards a model based approach for integration testing  

Science Journals Connector (OSTI)

In this paper, we introduce a model based approach for integration test cases generation. The approach is based on UML 2 Testing Profile and follows the Mode-Driven Architecture for generating integration test cases from unit test models. The generated ... Keywords: UTP, integration testing, model based testing, test cases generation

Mohamed Mussa; Ferhat Khendek

2011-07-01T23:59:59.000Z

192

Wind Speed Forecasting for Power System Operation  

E-Print Network [OSTI]

In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

Zhu, Xinxin

2013-07-22T23:59:59.000Z

193

Integrated Mathematical Modeling Software Series of Vehicle Propulsion...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Mathematical Modeling Software Series of Vehicle Propulsion System: (1) Tractive Effort (T sub ew) of Vehicle Road WheelTrack Sprocket Integrated Mathematical Modeling Software...

194

Electric Grid - Forecasting system licensed | ornl.gov  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Electric Grid - Forecasting system licensed Location Based Technologies has signed an agreement to integrate and market an Oak Ridge National Laboratory technology that provides...

195

Sandia National Laboratories: Solar Energy Forecasting and Resource...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

196

Sandia National Laboratories: Transmission Grid Integration  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

output profiles and forecasts to support solar integration studies. Tagged with: Energy * Grid Integration * photovoltaic * Photovoltaics * PV * Renewable Energy *...

197

Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model  

Science Journals Connector (OSTI)

Recently an actuator disk parameterization was implemented in the Weather Research and Forecasting (WRF) Model for large eddy simulation (LES) of wind turbine wakes. To thoroughly verify this model simulations of various types of turbines and atmospheric conditions must be evaluated against corresponding experimental data. In this work numerical simulations are compared to nacelle-based scanning lidar measurements taken in stable atmospheric conditions during a field campaign conducted at a wind farm in the western United States. Using several wake characteristics—such as the velocity deficit centerline location and wake width—as metrics for model verification the simulations show good agreement with the observations. Notable results include a high average velocity deficit decreasing from 73% at a downwind distance x of 1.2 rotor diameters (D) to 25% at x?=?6.6D resulting from a low average wind speed and therefore high average turbine thrust coefficient. Moreover the wake width expands from 1.4D at x?=?1.2D to 2.3D at x?=?6.6D. Finally new features—namely rotor tilt and drag from the nacelle and tower—are added to the existing actuator disk model in WRF-LES. Compared to the rotor the effect of the tower and nacelle on the flow is relatively small but nevertheless important for an accurate representation of the entire turbine. Adding rotor tilt to the model causes the vertical location of the wake center to shift upward. Continued advancement of the actuator disk model in WRF-LES will help lead to optimized turbine siting and controls at wind farms.

Matthew L. Aitken; Branko Kosovi?; Jeffrey D. Mirocha; Julie K. Lundquist

2014-01-01T23:59:59.000Z

198

Continuous reservoir simulation model updating and forecasting using a markov chain monte carlo method  

E-Print Network [OSTI]

).......................58 Fig. 29 - Mixed well objective function value vs. model number (static case) ....59 Fig. 30 - Histogram of cumulative oil production made by static case ................60 Fig. 31 - CDF of cumulative production by mixed well models...-well sampled models in the chain to quantify the uncertainty in future oil production. We use all the models in Fig. 2 except for the first 7,000 models, whose objective function value is significantly high. Unfortunately, even though the MCMC method is a...

Liu, Chang

2009-05-15T23:59:59.000Z

199

Probabilistic Verification of Global and Mesoscale Ensemble Forecasts of Tropical Cyclogenesis  

Science Journals Connector (OSTI)

Probabilistic forecasts of tropical cyclogenesis have been evaluated for two samples: a near-homogeneous sample of ECMWF and Weather Research and Forecasting (WRF) Model–ensemble Kalman filter (EnKF) ensemble forecasts during the National Science ...

Sharanya J. Majumdar; Ryan D. Torn

2014-10-01T23:59:59.000Z

200

Advances in NLTE Modeling for Integrated Simulations  

SciTech Connect (OSTI)

The last few years have seen significant progress in constructing the atomic models required for non-local thermodynamic equilibrium (NLTE) simulations. Along with this has come an increased understanding of the requirements for accurately modeling the ionization balance, energy content and radiative properties of different elements for a wide range of densities and temperatures. Much of this progress is the result of a series of workshops dedicated to comparing the results from different codes and computational approaches applied to a series of test problems. The results of these workshops emphasized the importance of atomic model completeness, especially in doubly excited states and autoionization transitions, to calculating ionization balance, and the importance of accurate, detailed atomic data to producing reliable spectra. We describe a simple screened-hydrogenic model that calculates NLTE ionization balance with surprising accuracy, at a low enough computational cost for routine use in radiation-hydrodynamics codes. The model incorporates term splitting, {Delta}n = 0 transitions, and approximate UTA widths for spectral calculations, with results comparable to those of much more detailed codes. Simulations done with this model have been increasingly successful at matching experimental data for laser-driven systems and hohlraums. Accurate and efficient atomic models are just one requirement for integrated NLTE simulations. Coupling the atomic kinetics to hydrodynamics and radiation transport constrains both discretizations and algorithms to retain energy conservation, accuracy and stability. In particular, the strong coupling between radiation and populations can require either very short timesteps or significantly modified radiation transport algorithms to account for NLTE material response. Considerations such as these continue to provide challenges for NLTE simulations.

Scott, H A; Hansen, S B

2009-07-08T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Radiolysis Model Formulation for Integration with the Mixed Potential Model  

SciTech Connect (OSTI)

The U.S. Department of Energy Office of Nuclear Energy (DOE-NE), Office of Fuel Cycle Technology has established the Used Fuel Disposition Campaign (UFDC) to conduct the research and development activities related to storage, transportation, and disposal of used nuclear fuel (UNF) and high-level radioactive waste. Within the UFDC, the components for a general system model of the degradation and subsequent transport of UNF is being developed to analyze the performance of disposal options [Sassani et al., 2012]. Two model components of the near-field part of the problem are the ANL Mixed Potential Model and the PNNL Radiolysis Model. This report is in response to the desire to integrate the two models as outlined in [Buck, E.C, J.L. Jerden, W.L. Ebert, R.S. Wittman, (2013) “Coupling the Mixed Potential and Radiolysis Models for Used Fuel Degradation,” FCRD-UFD-2013-000290, M3FT-PN0806058

Buck, Edgar C.; Wittman, Richard S.

2014-07-10T23:59:59.000Z

202

Atmospheric Environment 39 (2005) 13731382 A hierarchical Bayesian model to estimate and forecast ozone  

E-Print Network [OSTI]

reserved. Keywords: Statistical model; Space­time models; Air pollution; Ozone; Meteorology 1. Introduction describing the spatial­temporal behavior of ambient air pollutants such as ozone (O3) and particulate matter. Statistical space­time models are useful for illuminating relationships between different air pollutants

Irwin, Mark E.

203

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: * Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the

204

Design of a component-based integrated environmental modeling framework  

Science Journals Connector (OSTI)

Integrated environmental modeling (IEM) includes interdependent science-based components that comprise an appropriate software modeling system and are responsible for consuming and producing information as part of the system, but moving information from ... Keywords: FRAMES, IEM, Integrated environmental modeling, Multimedia modeling, Risk assessment

Gene Whelan, Keewook Kim, Mitch A. Pelton, Karl J. Castleton, Gerard F. Laniak, Kurt Wolfe, Rajbir Parmar, Justin Babendreier, Michael Galvin

2014-05-01T23:59:59.000Z

205

Synchronous and Asynchronous Integrations in an Ocean General Circulation Model  

Science Journals Connector (OSTI)

A basinwide ocean general circulation model of the North Pacific is used to study the difference in distributions of tracers between asynchronous and synchronous integrations. An integration in which equal time steps and no depth acceleration are ...

Yongfu Xu; Shigeaki Aoki; Koh Harada

2002-01-01T23:59:59.000Z

206

Modelling of Integrated Renewable Energy System  

Science Journals Connector (OSTI)

Energy is supplied in the form of electricity heat or fuels and an energy supply system must guarantee sufficient production and distribution of energy. An energy supply system based on renewable energy can be utilized as integrated renewable energy system (IRES) which can satisfy the energy needs of an area in appropriate & sustainable manner. Given the key role of renewable energy in rural electrification of remote rural areas the IRES for a given area can be modeled & optimized for meeting the energy needs. In the present paper Jaunpur block of Uttaranchal state of India has been selected as remote area. Based upon the data collected the resource potential and energy demand has been calculated & presented. The model on the basis of unit cost of the energy has been optimized using LINDO software 6.10 version. The results indicated that the optimized model has been found to the best choice for meeting the energy needs of the area. The results further indicated that for the above area either an IRES consisting of the above sources can provide a feasible solution in terms of energy fulfillments in the range of EPDF from 1.0 to 0.75.

A. K. Akella; R. P. Saini; M. P. Sharma

2007-01-01T23:59:59.000Z

207

Combining multiobjective optimization and Bayesian model averaging to calibrate forecast ensembles of  

E-Print Network [OSTI]

of soil hydraulic models Thomas Wo¨hling1 and Jasper A. Vrugt2 Received 12 May 2008; revised 8 September

Vrugt, Jasper A.

208

Power System Load Forecasting Based on EEMD and ANN  

Science Journals Connector (OSTI)

In order to fully mine the characteristics of load data and improve the accuracy of power system load forecasting, a load forecasting model based on Ensemble Empirical Mode ... is proposed in this paper. Firstly,...

Wanlu Sun; Zhigang Liu; Wenfan Li

2011-01-01T23:59:59.000Z

209

The Energy Demand Forecasting System of the National Energy Board  

Science Journals Connector (OSTI)

This paper presents the National Energy Board’s long term energy demand forecasting model in its present state of ... results of recent research at the NEB. Energy demand forecasts developed with the aid of this....

R. A. Preece; L. B. Harsanyi; H. M. Webster

1980-01-01T23:59:59.000Z

210

Evolutionary neural network modeling for forecasting the field failure data of repairable systems  

Science Journals Connector (OSTI)

An accurate product reliability prediction model can not only learn and track the product's reliability and operational performance, but also offer useful information for managers to take follow-up actions to improve the product' quality and cost. This ... Keywords: Genetic algorithms, Neural network model, Reliability prediction, Repairable system

L. Yi-Hui

2007-11-01T23:59:59.000Z

211

Time Series Models to Simulate and Forecast Wind Speed and Wind Power  

Science Journals Connector (OSTI)

A general approach for modeling wind speed and wind power is described. Because wind power is a function of wind speed, the methodology is based on the development of a model of wind speed. Values of wind power are estimated by applying the ...

Barbara G. Brown; Richard W. Katz; Allan H. Murphy

1984-08-01T23:59:59.000Z

212

Addressing model error through atmospheric stochastic physical parametrizations: impact on the coupled ECMWF seasonal forecasting system  

Science Journals Connector (OSTI)

...parametrizations: impact on the coupled ECMWF...Stochastic modelling and energy-efficient computing...effects of sub-grid-scale variability...present results of the impact of these schemes...and near-surface winds. Positive impact...Stochastic modelling and energy-efficient computing...

2014-01-01T23:59:59.000Z

213

Artificial Neural Network Model for Forecasting the Stock Price of Indian IT Company  

Science Journals Connector (OSTI)

The central issue of the study is to model the movement of stock price for Indian Information Technology (IT) companies. It has been observed that IT industry has some promising role in Indian economy. We apply t...

Joydeep Sen; Arup K. Das

2014-01-01T23:59:59.000Z

214

Marginalization and aggregation of exponential smoothing models in forecasting portfolio volatility  

Science Journals Connector (OSTI)

This paper examines exponentially weighted moving average models for predicting volatility and assessing risk in portfolios. It proposes a method that identifies the decay factors of the marginal volatility mo...

Giacomo Sbrana; Andrea Silvestrini

2012-01-01T23:59:59.000Z

215

Hydrologic modeling using triangulated irregular networks : terrain representation, flood forecasting and catchment response  

E-Print Network [OSTI]

Numerical models are modern tools for capturing the spatial and temporal variability in the land-surface hydrologic response to rainfall and understanding the physical relations between internal watershed processes and ...

Vivoni, Enrique R. (Enrique Rafael), 1975-

2003-01-01T23:59:59.000Z

216

Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction  

Science Journals Connector (OSTI)

Wind direction is an angular variable, as opposed to weather quantities such as temperature, quantitative precipitation, or wind speed, which are linear variables. Consequently, traditional model output statistics and ensemble postprocessing ...

Le Bao; Tilmann Gneiting; Eric P. Grimit; Peter Guttorp; Adrian E. Raftery

2010-05-01T23:59:59.000Z

217

The Application of Improved Grey GM(1,1) Model in Power System Load Forecast  

Science Journals Connector (OSTI)

According to existing Grey prediction model GM (1,1) in the data fluctuation, mutation, turning under uncertainty such as the problem of poor prediction accuracy, this paper presents an original data sequence ...

Zhengyuan Jia; Zhou Fan; Chuancai Li…

2012-01-01T23:59:59.000Z

218

Essays on macroeconomics and forecasting  

E-Print Network [OSTI]

explanatory variables. Compared to Stock and Watson (2002)�s models, the models proposed in this chapter can further allow me to select the factors structurally for each variable to be forecasted. I find advantages to using the structural dynamic factor...

Liu, Dandan

2006-10-30T23:59:59.000Z

219

Forecastability as a Design Criterion in Wind Resource Assessment: Preprint  

SciTech Connect (OSTI)

This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

Zhang, J.; Hodge, B. M.

2014-04-01T23:59:59.000Z

220

Revised {open_quotes}LEPS{close_quotes} scores for assessing climate model simulations and long-range forecasts  

SciTech Connect (OSTI)

The most commonly used measures for verifying forecasts or simulations of continuous variables are root-mean-squared error (rmse) and anomaly correlation. Some disadvantages of these measures are demonstrated. Existing assessment systems for categorical forecasts are discussed briefly. An alternative unbiased verification measure is developed, known as the linear error in probability space (LEPS) score. The LEPS score may be used to assess forecasts of both continuous and categorical variables and has some advantages over rmse and anomaly correlation. The properties of the version of LEPS discussed here are reviewed and compared with an earlier form of LEPS. A skill-score version of LEPS may be used to obtain an overall measure of the skill of a number of forecasts. This skill score is biased, but the bias is negligible if the number of effectively independent forecasts or simulations is large. Some examples are given in which the LEPS skill score is compared with rmse and anomaly correlation. 14 refs., 10 figs., 7 tabs.

Potts, J.M. [IACR-Rothamsted, Hertfordshire (United Kingdom)] [IACR-Rothamsted, Hertfordshire (United Kingdom); Folland, C.K. [Hadley Centre for Climate Prediction and Research, Berkshire (United Kingdom)] [Hadley Centre for Climate Prediction and Research, Berkshire (United Kingdom); Jolliffe, I.T. [Univ. of Aberdeen (United Kingdom)] [and others] [Univ. of Aberdeen (United Kingdom); and others

1996-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Formal Modeling and Analysis of the HLA Component Integration Standard  

E-Print Network [OSTI]

of domain-speci c integration standards in areas as diverse as programming environments, robotics control 20Formal Modeling and Analysis of the HLA Component Integration Standard Robert J. Allen IBM, Dept An increasingly important trend in the engineering of com- plex systems is the design of component integration

van der Hoek, André

222

Towards a Flexible Model for Data and Web Services Integration  

E-Print Network [OSTI]

a new framework that allows to integrate data and services. We use a language based on XML documentsTowards a Flexible Model for Data and Web Services Integration Serge Abiteboul, Omar Benjelloun that embeds service calls within semistructured data. The framework captures various integration scenarios

Abiteboul, Serge

223

A hybrid FLANN and adaptive differential evolution model for forecasting of stock market indices  

Science Journals Connector (OSTI)

This paper presents a computationally efficient functional link artificial neural network CEFLANN based adaptive model for financial time series prediction of leading Indian stock market indices. Financial time-series data are usually non-stationary ... Keywords: Adaptive Differential Evolution Ade, Artificial Neural Network, Functional Link Neural Network Flann, Least Mean Squares Lms, Technical Indicators

Ajit Kumar Rout; Birendra Biswal; Pradipta Kishore Dash

2014-01-01T23:59:59.000Z

224

A warranty forecasting model based on piecewise statistical distributions and stochastic simulation  

E-Print Network [OSTI]

industry and has a specific application to automotive electronics. The warranty prediction model is based is demonstrated using a case study of automotive electronics warranty returns. The approach developed b CALCE Electronic Products and Systems Center, Department of Mechanical Engineering, University

Sandborn, Peter

225

Modeling Utility Load and Temperature Relationships for Use with Long-Lead Forecasts  

Science Journals Connector (OSTI)

Models relating system-wide average temperature to total system load were developed for the Virginia Power and Duke Power service areas in the southeastern United States. Daily data for the 1985–91 period were used. The influence of temperature ...

Peter J. Robinson

1997-05-01T23:59:59.000Z

226

Univariate time-series forecasting of monthly peak demand of electricity in northern India  

Science Journals Connector (OSTI)

This study forecasts the monthly peak demand of electricity in the northern region of India using univariate time-series techniques namely Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) and Holt-Winters Multiplicative Exponential Smoothing (ES) for seasonally unadjusted monthly data spanning from April 2000 to February 2007. In-sample forecasting reveals that the MSARIMA model outperforms the ES model in terms of lower root mean square error, mean absolute error and mean absolute percent error criteria. It has been found that ARIMA (2, 0, 0) (0, 1, 1)12 is the best fitted model to explain the monthly peak demand of electricity, which has been used to forecast the monthly peak demand of electricity in northern India, 15 months ahead from February 2007. This will help Northern Regional Load Dispatch Centre to make necessary arrangements a priori to meet the future peak demand.

Sajal Ghosh

2008-01-01T23:59:59.000Z

227

Extreme wave events during hurricanes can seriously jeopardize the integrity and safety of offshore oil and gas operations in the Gulf of Mexico. Validation of wave forecast for  

E-Print Network [OSTI]

oil and gas operations in the Gulf of Mexico. Validation of wave forecast for significant wave heights of Mexico. Before the storm, it produced 148,000 barrels of oil equivalent per day and 160 million cubic over the warm Gulf of Mexico water between 26 and 28 August, and became a category 5 hurricane by 1200

228

Application of grey modeling method to fitting and forecasting wear trend of marine diesel engines  

Science Journals Connector (OSTI)

Oil monitoring is an important and useful method for predicting wear failure, and has been used in diesel engines successfully. The diesel engine is the key power equipment in ships and it is a complicated tribological system with uncertainty and indetermination. Grey system theory is suitable for systems in which some information is clear and some is not, so it is feasible to study the wear process of diesel engines with this theory. The unequal interval revised grey model (UIRGM) (1,1) is presented in this paper, which is applicable to original series with unequal intervals and sharp variation. The model that is built is applied to fit and predict element concentration as determined by oil spectrometric analysis. It is proved that UIRGM (1,1) determines the exact turning point, and the fitting and prediction results are acceptable.

Hong Zhang; Zhuguo Li; Zhaoneng Chen

2003-01-01T23:59:59.000Z

229

Integrated 3D Acid Fracturing Model for Carbonate Reservoir Stimulation  

E-Print Network [OSTI]

in integrating fracture propagation, acid transport and dissolution, and well performance models in a seamless fashion for acid fracturing design. In this new approach, the fracture geometry data of a hydraulic fracture is first obtained from commercial models...

Wu, Xi

2014-06-23T23:59:59.000Z

230

The Grid ENabled Integrated Earth System Modelling (GENIE) Framework  

Science Journals Connector (OSTI)

The Grid ENabled Integrated Earth system modelling (GENIE) framework is designed: (i) ... (ii) to tune and execute the resulting Earth system models on a wide variety of platforms including...

Tim Lenton

2013-01-01T23:59:59.000Z

231

Integrating Comprehensive Air Quality Modeling with Policy Analysis  

E-Print Network [OSTI]

Integrating Comprehensive Air Quality Modeling with Policy Analysis: Applications for Distributed Air Quality Modeling with Policy Analysis: Applications for Distributed Electricity Generation renewable technologies. These facilities also shift the magnitude, timing and location of air quality

232

Integrated Modeling and Simulation of Lunar Exploration Campaign Logistics  

E-Print Network [OSTI]

Integrated Modeling and Simulation of Lunar Exploration Campaign Logistics by Sarah A. Shull B #12;Integrated Modeling and Simulation of Lunar Exploration Campaign Logistics by Sarah A. Shull to establish a manned outpost on the lunar surface, it is essential to consider the logistics of both

de Weck, Olivier L.

233

Integrated Modeling and Simulation of Lunar Exploration Campaign Logistics  

E-Print Network [OSTI]

Integrated Modeling and Simulation of Lunar Exploration Campaign Logistics Sarah A. Shull, Olivier Campaign Logistics by Sarah A. Shull B.S.E. Aerospace Engineering (2001) The University of Michigan) #12;4 Integrated Modeling and Simulation of Lunar Exploration Campaign Logistics by Sarah A. Shull

234

Seamlessly Integrating Software & Hardware Modelling for Large-Scale Systems  

E-Print Network [OSTI]

Engineering, with the math- ematical modelling approach, Modelica, to address the software/hardware integration problem. The environment and hardware components are modelled in Modelica and integrated that a software/hardware combination with an 2nd International Workshop on Equation-Based Object-Oriented

Zhao, Yuxiao

235

Dynamic model order reduction for shipboard integrated power systems  

Science Journals Connector (OSTI)

The shipboard integrated power system is modeled by a system of differential-algebraic equations with dynamics having time constants varying from fractions of a second to several minutes. Control and simulation of naval shipboard power systems for different ... Keywords: electric ship, integrated power system, model order reduction, shipboard power system, singular perturbation

Sudipta Lahiri; Dagmar Niebur; Harry Kwatny; Gaurav Bajpai

2009-07-01T23:59:59.000Z

236

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation Evaluation Annual Energy Outlook Forecast Evaluation by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the impacts were not incorporated in the AEO projections until their enactment or effective dates in accordance with EIA's requirement to remain policy neutral and include only current laws and regulations in the AEO reference case projections.

237

Solid waste integrated forecast technical (SWEFT) report: FY1997 to FY 2070 - Document number changed to HNF-0918 at revision 1 - 1/7/97  

SciTech Connect (OSTI)

This web site provides an up-to-date report on the radioactive solid waste expected to be managed at Hanford`s Solid Waste (SW) Program from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the SW Program; program- level and waste class-specific estimates; background information on waste sources; and Li comparisons with previous forecasts and with other national data sources. The focus of this web site is on low- level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this site is reporting data current as of 9/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program`s life cycle.

Valero, O.J.

1996-10-03T23:59:59.000Z

238

Yield learning model for integrated circuit package  

E-Print Network [OSTI]

, and has a major influence on product perfo rmance and reliability. Increasing the yield in package assembly influence on product perfo will reduce the effective manufacturing cost during assembly. Hence integrated circuit manufacturers try to improve...

Balasubramaniam, Gaurishankar

2012-06-07T23:59:59.000Z

239

Forecasting wind speed financial return  

E-Print Network [OSTI]

The prediction of wind speed is very important when dealing with the production of energy through wind turbines. In this paper, we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model that has been shown to be able to reproduce accurately the statistical behavior of wind speed. The model is used to forecast, one step ahead, wind speed. In order to check the validity of the model we show, as indicator of goodness, the root mean square error and mean absolute error between real data and predicted ones. We also compare our forecasting results with those of a persistence model. At last, we show an application of the model to predict financial indicators like the Internal Rate of Return, Duration and Convexity.

D'Amico, Guglielmo; Prattico, Flavio

2013-01-01T23:59:59.000Z

240

Integrated Model to Access the Global Environment | Open Energy Information  

Open Energy Info (EERE)

Integrated Model to Access the Global Environment Integrated Model to Access the Global Environment Jump to: navigation, search LEDSGP green logo.png FIND MORE DIA TOOLS This tool is part of the Development Impacts Assessment (DIA) Toolkit from the LEDS Global Partnership. Tool Summary LAUNCH TOOL Name: Integrated Model to Access the Global Environment (IMAGE) Agency/Company /Organization: PBL Netherlands Environmental Assessment Agency Focus Area: Biomass Complexity/Ease of Use: Advanced Website: themasites.pbl.nl/en/themasites/image/index.html Cost: Paid Equivalent URI: cleanenergysolutions.org/content/integrated-model-access-global-enviro Related Tools ENV-Linkages-KEI Model World Induced Technical Change Hybrid (WITCH) Global Trade and Analysis Project (GTAP) Model ... further results IMAGE is an ecological-environmental framework that simulates the

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Modeling for Tsunami Forecast  

E-Print Network [OSTI]

, accuracy, special operating environment needs, ease-of-use, and documentation #12;December 26, 2004 Sumatra

242

Integrated Nozzle Flow, Spray, Combustion, & Emission Modeling...  

Broader source: Energy.gov (indexed) [DOE]

Combustion, and Emission Modeling Using KH-ACT Primary Breakup Model & Detailed Chemistry Sibendu Som, Douglas E. Longman Engine and Emissions Group (Energy Systems Division)...

243

Annual Energy Outlook Forecast Evaluation 2004  

Gasoline and Diesel Fuel Update (EIA)

2004 2004 * The Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) has produced annual evaluations of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and replacing the historical year of data with the most recent. The forecast evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute percent errors for several of the major variables for AEO82 through AEO2004. (There is no report titled Annual Energy Outlook 1988 due to a change in the naming convention of the AEOs.) The average absolute percent error is the simple mean of the absolute values of the percentage difference between the Reference Case projection and the

244

energy data + forecasting | OpenEI Community  

Open Energy Info (EERE)

energy data + forecasting energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. Links: FRED beta demo energy data + forecasting Syndicate content 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2084382122

245

Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint  

SciTech Connect (OSTI)

The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

2014-05-01T23:59:59.000Z

246

18 Bureau of Meteorology Annual Report 201314 Hazards, warnings and forecasts  

E-Print Network [OSTI]

and numerical prediction models. #12;19Bureau of Meteorology Annual Report 2013­14 2 Performance Performance programs: · Weather forecasting services; · Flood forecasting and warning services; · Hazard prediction, Warnings and Forecasts portfolio provides a range of forecast and warning services covering weather, ocean

Greenslade, Diana

247

A Stochastic Unit Commitment Model for Integrating Renewable Supply  

E-Print Network [OSTI]

A Stochastic Unit Commitment Model for Integrating Renewable Supply and Demand Response Anthony from the large-scale integration of renewable energy sources and deferrable demand in power systems. We- sorbing the uncertainty and variability associated with renewable supply: centralized co

Oren, Shmuel S.

248

Towards a formal integrated model of collaborative healthcare workflows  

Science Journals Connector (OSTI)

Health information systems (HIS) are becoming increasingly integrated through network communication technologies. Collaborative healthcare workflows (CHWF) are inherently complex, involving interactions among human actors, and (legacy) digital and physical ... Keywords: CSP, collaborative workflows, formal verification, infrastructure model, integrated health information systems

Cristiano Bertolini; Martin Schäf; Volker Stolz

2011-08-01T23:59:59.000Z

249

Cost Modeling and Design Techniques for Integrated Package Distribution Systems  

E-Print Network [OSTI]

Cost Modeling and Design Techniques for Integrated Package Distribution Systems Karen R. Smilowitz and Carlos F. Daganzo December 23, 2005 Abstract Complex package distribution systems are designed using-scale integrated distribution networks. While the network design problem is quite complex, we demonstrate

Smilowitz, Karen

250

Asia-Pacific Integrated Model (AIM) | Open Energy Information  

Open Energy Info (EERE)

Asia-Pacific Integrated Model (AIM) Asia-Pacific Integrated Model (AIM) Jump to: navigation, search Tool Summary Name: Asia-Pacific Integrated Model (AIM) Agency/Company /Organization: National Institute of Environmental Studies (NIES) User Interface: Spreadsheet Complexity/Ease of Use: Advanced Website: www-iam.nies.go.jp/aim/index.htm Country: Asia Locality: Asia-Pacific Cost: Free UN Region: Eastern Asia Related Tools SimCLIM Poverty Social Impact Analysis Threshold 21 Model ... further results Find Another Tool FIND DEVELOPMENT IMPACTS ASSESSMENT TOOLS A large-scale computer simulation model for assessing policy options to stabilize the global climate through greenhouse gas emissions reduction, with an emphasis on the Asia-Pacific region. Approach AIM comprises three main models: a greenhouse gas emissions model

251

Automated inter-model parameter connection synthesis for simulation model integration  

E-Print Network [OSTI]

New simulation modeling environments have been developed such that multiple models can be integrated into a single model. This conglomeration of model data allows designers to better understand the physical phenomenon being ...

Ligon, Thomas (Thomas Crumrine)

2007-01-01T23:59:59.000Z

252

Forecasting energy markets using support vector machines  

Science Journals Connector (OSTI)

Abstract In this paper we investigate the efficiency of a support vector machine (SVM)-based forecasting model for the next-day directional change of electricity prices. We first adjust the best autoregressive SVM model and then we enhance it with various related variables. The system is tested on the daily Phelix index of the German and Austrian control area of the European Energy Exchange (???) wholesale electricity market. The forecast accuracy we achieved is 76.12% over a 200 day period.

Theophilos Papadimitriou; Periklis Gogas; Efthimios Stathakis

2014-01-01T23:59:59.000Z

253

ANL Wind Power Forecasting and Electricity Markets | Open Energy  

Open Energy Info (EERE)

ANL Wind Power Forecasting and Electricity Markets ANL Wind Power Forecasting and Electricity Markets Jump to: navigation, search Logo: Wind Power Forecasting and Electricity Markets Name Wind Power Forecasting and Electricity Markets Agency/Company /Organization Argonne National Laboratory Partner Institute for Systems and Computer Engineering of Porto (INESC Porto) in Portugal, Midwest Independent System Operator and Horizon Wind Energy LLC, funded by U.S. Department of Energy Sector Energy Focus Area Wind Topics Pathways analysis, Technology characterizations Resource Type Software/modeling tools Website http://www.dis.anl.gov/project References Argonne National Laboratory: Wind Power Forecasting and Electricity Markets[1] Abstract To improve wind power forecasting and its use in power system and electricity market operations Argonne National Laboratory has assembled a team of experts in wind power forecasting, electricity market modeling, wind farm development, and power system operations.

254

NREL: Transmission Grid Integration - Generator Modeling  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Generator Modeling Generator Modeling NREL works with the solar and wind industries to provide utilities and grid operators with generator models to help them analyze the impact of variable generation on power system performance and reliability. As the amount of variable generation increases, the need for such models increases. Ensuring the models are as generic as possible allows for ease of use, model validation, data exchange, and analysis. To address this need, NREL researchers are developing generic dynamic models of wind and solar power plants. NREL's dynamic modeling efforts include: Collecting wind plant output data with corresponding wind resource data (speed, direction, and air density) from meteorological towers and performing multivariate analysis of the data to develop an equivalent wind

255

Scalable computational architecture for integrating biological pathway models  

E-Print Network [OSTI]

A grand challenge of systems biology is to model the cell. The cell is an integrated network of cellular functions. Each cellular function, such as immune response, cell division, metabolism or apoptosis, is defined by an ...

Shiva, V. A

2007-01-01T23:59:59.000Z

256

An integrated cost model for software reuse  

Science Journals Connector (OSTI)

Several cost models have been proposed in the past for estimating, predicting, and analyzing the costs of software reuse. In this paper we analyze existing models, explain their variance, and propose a tool-supported comprehensive model that encompasses ... Keywords: COCOMO, application engineering, component engineering, domain engineering, return on investment, software cost estimation, software reuse

A. Mili; S. Fowler Chmiel; R. Gottumukkala; L. Zhang

2000-06-01T23:59:59.000Z

257

Use of wind power forecasting in operational decisions.  

SciTech Connect (OSTI)

The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V. (Decision and Information Sciences); (INESC Porto)

2011-11-29T23:59:59.000Z

258

Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications  

Science Journals Connector (OSTI)

A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011) the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems one vertically profiling and another operated over a variety of scanning modes were utilized to obtain forcing for the simulations and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of 20?W m?2 and 100?W m?2 were used to examine the sensitivity of the simulated wakes to convective instability. Simulations using the smaller heat flux values showed good agreement with wake deficits observed during TWICS-2011 whereas those using the larger value showed enhanced spreading and more-rapid attenuation. This study demonstrates the utility of actuator models implemented within atmospheric LES to address a range of atmospheric science and engineering applications. Validated implementation of the GAD in a numerical weather prediction code such as WRF will enable a wide range of studies related to the interaction of wind turbines with the atmosphere and surface.

J. D. Mirocha; B. Kosovic; M. L. Aitken; J. K. Lundquist

2014-01-01T23:59:59.000Z

259

Solar forecasting review  

E-Print Network [OSTI]

2.1.2 European Solar Radiation Atlas (ESRA)2.4 Evaluation of Solar Forecasting . . . . . . . . .2.4.1 Solar Variability . . . . . . . . . . . . .

Inman, Richard Headen

2012-01-01T23:59:59.000Z

260

Energy Demand Forecasting  

Science Journals Connector (OSTI)

This chapter presents alternative approaches used in forecasting energy demand and discusses their pros and cons. It... Chaps. 3 and 4 ...

S. C. Bhattacharyya

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Short term forecasting of solar radiation based on satellite data  

E-Print Network [OSTI]

Short term forecasting of solar radiation based on satellite data Elke Lorenz, Annette Hammer University, D-26111 Oldenburg Forecasting of solar irradiance will become a major issue in the future integration of solar energy resources into existing energy supply structures. Fluctuations of solar irradiance

Heinemann, Detlev

262

Quantifying Uncertainty for Climate Change and Long-Range Forecasting Scenarios with Model Errors. Part I: Gaussian Models  

E-Print Network [OSTI]

of a turbulent tracer with a mean gradient with the background turbulent field velocity generated by the first. An important feature of all the current computer Atmosphere Ocean Science (AOS) models (Neelin et al. 2006 or the limitations of computing power with the necessary parameterization of subgrid processes. Examples of important

Majda, Andrew J.

263

Improving Inventory Control Using Forecasting  

E-Print Network [OSTI]

This project studied and analyzed Electronic Controls, Inc.’s forecasting process for three high-demand products. In addition, alternative forecasting methods were developed to compare to the current forecast method. The ...

Balandran, Juan

2005-12-16T23:59:59.000Z

264

Integrate Experiments and Models to Estimate Exposure - (1) Building  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Integrate Experiments and Models to Estimate Exposure - (1) Building Integrate Experiments and Models to Estimate Exposure - (1) Building Fumigation and (2) Elemental Mercury Spill Speaker(s): Wanyu Chan Date: February 22, 2010 - 12:00pm Location: 90-3075 Seminar Host/Point of Contact: Michael Sohn Models that predict exposure concentrations in the indoor and outdoor air can be improved by experiments designed to validate or calibrate the models. This presentation will showcase two examples where experiments and models are integrated to estimate exposure concentrations. One example is the use of methyl bromide as fumigant at food processing facilities. Field studies were conducted at three mill sites that are representative of typical industry practices in terms of size, operation, and fumigation protocol. Concentrations of methyl bromide inside the mills and outdoors

265

Integrated Global System Modeling Framework | Open Energy Information  

Open Energy Info (EERE)

Integrated Global System Modeling Framework Integrated Global System Modeling Framework Jump to: navigation, search LEDSGP green logo.png FIND MORE DIA TOOLS This tool is part of the Development Impacts Assessment (DIA) Toolkit from the LEDS Global Partnership. Tool Summary LAUNCH TOOL Name: Integrated Global System Modeling Framework Agency/Company /Organization: MIT Joint Program on the Science and Policy of Global Change Sector: Climate, Energy Focus Area: Renewable Energy Phase: Determine Baseline, Evaluate Options Topics: - Macroeconomic Resource Type: Software/modeling tools User Interface: Desktop Application Complexity/Ease of Use: Not Available Website: globalchange.mit.edu/research/IGSM Cost: Free Related Tools Transport Co-benefits Calculator General Equilibrium Modeling Package (GEMPACK)

266

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) MS Excel Viewer PDF (Acrobat Reader required Download Acrobat Reader ) Adobe Acrobat Reader Logo Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF

267

Next Generation Short-Term Forecasting of Wind Power Overview of the ANEMOS Project.  

E-Print Network [OSTI]

1 Next Generation Short-Term Forecasting of Wind Power ­ Overview of the ANEMOS Project. G outperform current state-of-the-art methods, for onshore and offshore wind power forecasting. Advanced forecasts for the power system management and market integration of wind power. Keywords: Wind power, short

Boyer, Edmond

268

VALIDATION OF SHORT AND MEDIUM TERM OPERATIONAL SOLAR RADIATION FORECASTS IN THE US  

E-Print Network [OSTI]

, and medium term forecasts (up to seven days ahead) from numerical weather prediction models [1]. Forecasts radiation forecasting. One approach relies on numerical weather prediction (NWP) models which can be global modeling of the atmosphere. NWP models cannot, at this stage of their development, predict the exact

Perez, Richard R.

269

Technology Forecasting Scenario Development  

E-Print Network [OSTI]

Technology Forecasting and Scenario Development Newsletter No. 2 October 1998 Systems Analysis was initiated on the establishment of a new research programme entitled Technology Forecasting and Scenario and commercial applica- tion of new technology. An international Scientific Advisory Panel has been set up

270

CAPP 2010 Forecast.indd  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Forecast, Markets & Pipelines 1 Crude Oil Forecast, Markets & Pipelines June 2010 2 CANADIAN ASSOCIATION OF PETROLEUM PRODUCERS Disclaimer: This publication was prepared by the...

271

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height  

Science Journals Connector (OSTI)

The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements in wind speed forecasts at a typical wind turbine hub height (80 m). An ensemble consisting of WRF model simulations with ...

Adam J. Deppe; William A. Gallus Jr.; Eugene S. Takle

2013-02-01T23:59:59.000Z

272

Workshop on Carbon Sequestration Science - Modeling and Integrated Assessment  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Modeling and Integrated Modeling and Integrated Assessment Howard Herzog MIT Energy Laboratory May 24, 2001 Economic Assessments * Engineering analysis of CO 2 separation and capture * Economic modeling/ integrated assessment of carbon capture and sequestration * Comparison on equal basis of the major sequestration options Economic Modeling Motivation * When might carbon capture and sequestration (CCS) become competitive? * What is its potential scale? * Which technologies look most promising? . . . . And when? * How to see the potential in a general market context? Detailed Reference *Sean Biggs Thesis: S Biggs, S. D., "Sequestering Carbon from Power Plants: The Jury is Still Out," M.I.T. Masters Thesis, (2000). S http://sequestration.mit.edu/pdf/SeanBiggs.pdf What Determines Competitiveness?

273

Modeling Energy Conservation in a Completely Integrable Boussinesq system  

E-Print Network [OSTI]

Modeling Energy Conservation in a Completely Integrable Boussinesq system Alfatih Ali and Henrik Kalisch Department of Mathematics, University of Bergen Postbox 7800, 5020 Bergen, Norway March 23, 2013 Abstract This work presents a derivation of the energy density and energy flux of surface waves modeled

Kalisch, Henrik

274

Pseudo-Differential Operators and Integrable Models  

E-Print Network [OSTI]

The importance of the theory of pseudo-differential operators in the study of non linear integrable systems is point out. Principally, the algebra $\\Xi $ of nonlinear (local and nonlocal) differential operators, acting on the ring of analytic functions $u_{s}(x, t)$, is studied. It is shown in particular that this space splits into several classes of subalgebras $\\Sigma_{jr}, j=0,\\pm 1, r=\\pm 1$ completely specified by the quantum numbers: $s$ and $(p,q)$ describing respectively the conformal weight (or spin) and the lowest and highest degrees. The algebra ${\\huge \\Sigma}_{++}$ (and its dual $\\Sigma_{--}$) of local (pure nonlocal) differential operators is important in the sense that it gives rise to the explicit form of the second hamiltonian structure of the KdV system and that we call also the Gelfand-Dickey Poisson bracket. This is explicitly done in several previous studies, see for the moment \\cite{4, 5, 14}. Some results concerning the KdV and Boussinesq hierarchies are derived explicitly.

M. B. Sedra

2009-12-18T23:59:59.000Z

275

Integration of Nonlinear CDU Models in Refinery  

E-Print Network [OSTI]

Hydrotreatment Distillate blending Gas oil blending Cat Crack CDU Crude1, ... Crude2, .... butane Fuel gas Prem. Gasoline Reg. Gasoline Distillate Fuel Oil Treated Residuum SR Fuel gas SR Naphtha SR Gasoline SR Distillate SR GO SR Residuum Product Blending 4 #12;Planning Model Example Information Given Refinery

Grossmann, Ignacio E.

276

INTEGRATION OF FACILITY MODELING CAPABILITIES FOR NUCLEAR NONPROLIFERATION ANALYSIS  

SciTech Connect (OSTI)

Developing automated methods for data collection and analysis that can facilitate nuclear nonproliferation assessment is an important research area with significant consequences for the effective global deployment of nuclear energy. Facility modeling that can integrate and interpret observations collected from monitored facilities in order to ascertain their functional details will be a critical element of these methods. Although improvements are continually sought, existing facility modeling tools can characterize all aspects of reactor operations and the majority of nuclear fuel cycle processing steps, and include algorithms for data processing and interpretation. Assessing nonproliferation status is challenging because observations can come from many sources, including local and remote sensors that monitor facility operations, as well as open sources that provide specific business information about the monitored facilities, and can be of many different types. Although many current facility models are capable of analyzing large amounts of information, they have not been integrated in an analyst-friendly manner. This paper addresses some of these facility modeling capabilities and illustrates how they could be integrated and utilized for nonproliferation analysis. The inverse problem of inferring facility conditions based on collected observations is described, along with a proposed architecture and computer framework for utilizing facility modeling tools. After considering a representative sampling of key facility modeling capabilities, the proposed integration framework is illustrated with several examples.

Gorensek, M.; Hamm, L.; Garcia, H.; Burr, T.; Coles, G.; Edmunds, T.; Garrett, A.; Krebs, J.; Kress, R.; Lamberti, V.; Schoenwald, D.; Tzanos, C.; Ward, R.

2011-07-18T23:59:59.000Z

277

Simulation and Modeling Techniques for Signal Integrity and Electromagnetic Interference on High Frequency Electronic Systems.  

E-Print Network [OSTI]

Simulation and Modeling Techniques for Signal Integrity and Electromagnetic Interference on High and Modeling Techniques for Signal Integrity and Electromagnetic Interference on High Frequency Electronic Integrity and Electromagnetic Interference on High Frequency Electronic Systems. by Luca Daniel Doctor

Daniel, Luca

278

Integrated cluster analysis and artificial neural network modeling for steam-assisted gravity drainage performance prediction in heterogeneous reservoirs  

Science Journals Connector (OSTI)

Abstract Evaluation of steam-assisted gravity drainage (SAGD) performance that involves detailed compositional simulations is usually deterministic, cumbersome, expensive (manpower and time consuming), and not quite suitable for practical decision making and forecasting, particularly when dealing with high-dimensional data space consisting of large number of operational and geological parameters. Data-driven modeling techniques, which entail comprehensive data analysis and implementation of machine learning methods for system forecast, provide an attractive alternative. In this paper, artificial neural network (ANN) is employed to predict SAGD production in heterogeneous reservoirs, an important application that is lacking in existing literature. Numerical flow simulations are performed to construct a training data set consists of various attributes describing characteristics associated with reservoir heterogeneities and other relevant operating parameters. Empirical Arps decline parameters are tested successfully for parameterization of cumulative production profile and considered as outputs of the ANN models. Sensitivity studies on network configurations are also investigated. Principal components analysis (PCA) is performed to reduce the dimensionality of the input vector, improve prediction quality, and limit over-fitting. In a case study, reservoirs with distinct heterogeneity distributions are fed to the model. It is shown that robustness and accuracy of the prediction capability are greatly enhanced when cluster analysis are performed to identify internal data structures and groupings prior to ANN modeling. Both deterministic and fuzzy-based clustering techniques are compared, and separate ANN model is constructed for each cluster. The model is then tested using a validation data set (cases that have not been used during the training stage). The proposed approach can be integrated directly into most existing reservoir management routines. In addition, incorporating techniques for dimensionality reduction and clustering with ANN demonstrates the viability of this approach for analyzing large field data set. Given that quantitative ranking of operating areas, robust forecasting, and optimization of heavy oil recovery processes are major challenges faced by the industry, the proposed research highlights the significant potential of applying effective data-driven modeling approaches in analyzing other solvent-additive steam injection projects.

Ehsan Amirian; Juliana Y. Leung; Stefan Zanon; Peter Dzurman

2015-01-01T23:59:59.000Z

279

Performance Modeling for Exascale Autotuning: An Integrated Approach |  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Performance Modeling for Exascale Autotuning: An Integrated Approach Performance Modeling for Exascale Autotuning: An Integrated Approach Title Performance Modeling for Exascale Autotuning: An Integrated Approach Publication Type Miscellaneous Year of Publication 2013 Authors Balaprakash, P, Wild, SM, Hovland, PD Other Numbers ANL/MCS-P5000-0813 Abstract The usual suspects - shrinking integrated circuit feature sizes, heterogeneous nodes with many-core processors, deep memory hierarchies, an ever-present power wall, energy efficiency demands, and resiliency concerns - make exascale application and system co-design a daunting, complex task. Providing effective model-driven prediction and optimization capabilities at runtime and a software stack that includes model-informed autotuning are key to mitigating this complexity. We define autotuning for application-system co-design as a systematic process of navigating the space defined by other software and hardware parameters that affect the performance metrics of the application and the system. Autotuning should orchestrate hardware and software-provided knobs to reduce execution time, power draw, energy consumption, and other constituent features, such as memory footprints. Current autotuning approaches, however, are unlikely to be successful for application-system co-design at exascale: the number of parameters exposed at the hardware and software levels will be large, drastically increasing the decision space; rigorous approaches to optimizing multiple conflicting objectives simultaneously are absent; and there is a lack of multiple-metric performance models. Significant research is required to develop an integrated modeling, machine learning, and search approach in order to provide model-driven prediction and optimization capabilities at runtime.

280

Reformulated Gasoline Complex Model  

Gasoline and Diesel Fuel Update (EIA)

Refiners Switch to Reformulated Refiners Switch to Reformulated Gasoline Complex Model Contents * Summary * Introduction o Table 1. Comparison of Simple Model and Complex Model RFG Per Gallon Requirements * Statutory, Individual Refinery, and Compliance Baselines o Table 2. Statutory Baseline Fuel Compositions * Simple Model * Complex Model o Table 3. Complex Model Variables * Endnotes Related EIA Short-Term Forecast Analysis Products * RFG Simple and Complex Model Spreadsheets * Areas Particpating in the Reformulated Gasoline Program * Environmental Regulations and Changes in Petroleum Refining Operations * Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model * Reformulated Gasoline Foreign Refinery Rules * Demand, Supply, and Price Outlook for Reformulated Motor Gasoline, 1995 , (Adobe

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Map algebra and model algebra for integrated model building  

Science Journals Connector (OSTI)

Computer models are important tools for the assessment of environmental systems. A seamless workflow of construction and coupling of model components is essential for environmental scientists. However, currently available software packages are often ... Keywords: Biomass-harvest model, Component-based modelling, PCRaster, Python, Spatio-temporal simulation

Oliver Schmitz; Derek Karssenberg; Kor De Jong; Jean-Luc De Kok; Steven M. De Jong

2013-10-01T23:59:59.000Z

282

A robust automatic phase-adjustment method for financial forecasting  

Science Journals Connector (OSTI)

In this work we present the robust automatic phase-adjustment (RAA) method to overcome the random walk dilemma for financial time series forecasting. It consists of a hybrid model composed of a qubit multilayer perceptron (QuMLP) with a quantum-inspired ... Keywords: Financial forecasting, Hybrid models, Quantum-inspired evolutionary algorithm, Qubit multilayer perceptron, Random walk dilemma

Ricardo de A. Araújo

2012-03-01T23:59:59.000Z

283

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center  

E-Print Network [OSTI]

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

Washington at Seattle, University of

284

Valuing Climate Forecast Information  

Science Journals Connector (OSTI)

The article describes research opportunities associated with evaluating the characteristics of climate forecasts in settings where sequential decisions are made. Illustrative results are provided for corn production in east central Illinois. ...

Steven T. Sonka; James W. Mjelde; Peter J. Lamb; Steven E. Hollinger; Bruce L. Dixon

1987-09-01T23:59:59.000Z

285

Comparing Forecast Skill  

Science Journals Connector (OSTI)

A basic question in forecasting is whether one prediction system is more skillful than another. Some commonly used statistical significance tests cannot answer this question correctly if the skills are computed on a common period or using a common ...

Timothy DelSole; Michael K. Tippett

2014-12-01T23:59:59.000Z

286

An Integrated Framework for Parametric Design Using Building Energy Models  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

An Integrated Framework for Parametric Design Using Building Energy Models An Integrated Framework for Parametric Design Using Building Energy Models Speaker(s): Bryan Eisenhower Date: September 22, 2011 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Michael Wetter In this talk we will present a framework for analyses of building energy models including uncertainty and sensitivity analysis, optimization, calibration, and failure mode effect analysis. The methodology begins with efficient uniformly ergodic numerical sampling and regression analysis based on machine learning to derive an analytic representation of the full energy model (e.g. EnergyPlus, TRNSYS, etc). Once these steps are taken, and an analytical representation of the dynamics is obtained, multiple avenues for analysis are opened that were previously impeded by the

287

Techno-economic modelling of integrated advanced power cycles  

Science Journals Connector (OSTI)

Concerns regarding the environmental impacts of power generation have stimulated interest in energy efficient cycles such as the integrated gasification combined cycle (IGCC) and the integrated gasification humid air turbine (IGHAT) cycle. These advanced power cycles are complex owing to the large number of units involved, interactions among the units, and the presence of streams of diverse compositions and properties. In this paper, techno-economic computer models of IGCC and IGHAT cycles are presented along with some sample results that illustrate the models' capabilities. The models, which were validated using actual data, provide performance predictions, inventories of capital and operating costs, as well as levels of gaseous emissions and solid wastes. While the models are simple enough for use in parametric, sensitivity and optimisation studies, they are responsive to variations in coal characteristics, design and operating conditions, part load operations and financial parameters.

A.O. Ong'iro; V.I. Ugursal; A.M. Al Taweel

2001-01-01T23:59:59.000Z

288

A study of Shanghai fuel oil futures price volatility based on high frequency data: Long-range dependence, modeling and forecasting  

Science Journals Connector (OSTI)

In existing researches, the investigations of oil price volatility are always performed based on daily data and squared daily return is always taken as the proxy of actual volatility. However, it is widely accepted that the popular realized volatility (RV) based on high frequency data is a more robust measure of actual volatility than squared return. Due to this motivation, we investigate dynamics of daily volatility of Shanghai fuel oil futures prices employing 5-minute high frequency data. First, using a nonparametric method, we find that RV displays strong long-range dependence and recent financial crisis can cause a lower degree of long-range dependence. Second, we model daily volatility using RV models and GARCH-class models. Our results indicate that RV models for intraday data overwhelmingly outperform GARCH-class models for daily data in forecasting fuel oil price volatility, regardless the proxy of actual volatility. Finally, we investigate the major source of such volatile prices and found that trader activity has major contribution to fierce variations of fuel oil prices.

Li Liu; Jieqiu Wan

2012-01-01T23:59:59.000Z

289

Forecast of Advanced Technology for Coal Power Generation Towards the Year of 2050 in CO2 Reduction Model of Japan  

Science Journals Connector (OSTI)

Abstract In the fossil fuel, coal is enough to get easily because it has supply and price stability brought about its ubiquitously. Coal is used for power generation as the major fuel in the world. However it is true that control of global warming should be applied to coal power generations. Therefore, many people expect CO2 reduction by technical innovation such as efficiency improvement, Carbon dioxide Capture and Storage (CCS). In case of coal power plant are considered for improving efficiency. Some of them have already put into commercial operation but others are still under R&D stage. Especially, the technical development prospect of the power plant is very important for planning the energy strategy in the resource-importing country. Japan Coal Energy Center (JCOAL) constructed a program to forecast the share of advanced coal fired plants/natural gas power plants towards the year of 2050. Then, we simulated the future prediction about 2 cases (the Japanese scenario and the world scenario). The fuel price and the existence of CCS were considered in the forecast of the technical development of the thermal power generation. Especially in the Japanese scenario, we considered the CO2 reduction target which is 80% reduction in 1990. In the world scenario, coal price had almost no influence on the share of coal fired plant. However, when the gas price increased 1.5% or more, the share of coal fired plant increased. In that case, CO2 emissions increased because coal-fired plant increased. Compared with both cases, the amount of CO2 in 2050 without CCS case was 50% higher than that of with CCS case. In Japanese scenario, achievement of 80% CO2 reduction target is impossible without CCS. If CCS is introduced into all the new establishment coal fired plant, CO2 reduction target can be attained. In the Japanese scenario, the gas price more expensive than a coal price so that the amount of the coal fired plant does not decline. Since the reduction of the amount of CO2 will be needed in all over the world, introductory promotion and technical development of CCS are very important not only Japan but also all over the world.

Takashi Nakamura; Keiji Makino; Kunihiko Shibata; Michiaki Harada

2013-01-01T23:59:59.000Z

290

Cost Modeling and Design Techniques for Integrated Package Distribution Systems  

E-Print Network [OSTI]

Cost Modeling and Design Techniques for Integrated Package Distribution Systems Karen R. Smilowitz idealizations of network geometries, operating costs, demand and customer distributions, and routing patterns that approximate the total cost of operation. The design problem is then reduced to a series of optimization

Daganzo, Carlos F.

291

Incorporating Carbon Capture and Storage Technologies in Integrated Assessment Models  

E-Print Network [OSTI]

Incorporating Carbon Capture and Storage Technologies in Integrated Assessment Models J. R. Mc climate policy analysis. This paper examines the representation of carbon capture and storage (CCS carbon capture and storage, 2) a natural gas combined cycle technology with carbon capture and storage 1

292

Integrated Modeling and Design of Nonlinear Control Systems  

E-Print Network [OSTI]

Integrated Modeling and Design of Nonlinear Control Systems Gilmer L. Blankenship Harry G. Kwatny building, simulation, control system design and real time implementation. Software Environment Overview: A summary description of a symbolic computing environment for nonlinear control system design is provided

Kwatny, Harry G.

293

An Integrated Approach for Creating Model Diesel Fuels  

Science Journals Connector (OSTI)

An Integrated Approach for Creating Model Diesel Fuels ... There is growing recognition that the optimal fuel properties (i) are dependent on the engine operating conditions and (ii) can be different for different parts of the drive cycle. ... The total solution to this problem belongs to the general and very difficult class of mixed-integer nonlinear problems (MINLP). ...

Ioannis P. Androulakis; Mark D. Weisel; Chang S. Hsu; Kuangnan Qian; Larry A. Green; John T. Farrell; Kiyomi Nakakita

2004-11-19T23:59:59.000Z

294

A Unit Commitment Model with Demand Response for the Integration of Renewable Energies  

E-Print Network [OSTI]

The output of renewable energy fluctuates significantly depending on weather conditions. We develop a unit commitment model to analyze requirements of the forecast output and its error for renewable energies. Our model obtains the time series for the operational state of thermal power plants that would maximize the profits of an electric power utility by taking into account both the forecast of output its error for renewable energies and the demand response of consumers. We consider a power system consisting of thermal power plants, photovoltaic systems (PV), and wind farms and analyze the effect of the forecast error on the operation cost and reserves. We confirm that the operation cost was increases with the forecast error. The effect of a sudden decrease in wind power is also analyzed. More thermal power plants need to be operated to generate power to absorb this sudden decrease in wind power. The increase in the number of operating thermal power plants within a short period does not affect the total opera...

Ikeda, Yuichi; Kataoka, Kazuto; Ogimoto, Kazuhiko

2011-01-01T23:59:59.000Z

295

An Integrated Modeling Framework for Carbon Capture and Storage Technologies  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Karen L. cohen Karen L. cohen Project Manager National Energy Technology Laboratory 626 Cochrans Mill Road P.O. Box 10940 Pittsburgh, PA 15236 412-386-6667 karen.cohen@netl.doe.gov Edward s. Rubin Carnegie Mellon University 5000 Forbes Avenue 128A Baker Hall Pittsburgh, PA 15213 412-268-5897 rubin@cmu.edu An IntegrAted ModelIng FrAMework For CArbon CApture And StorAge teChnologIeS Background The U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) is developing safe, lower-cost methods of carbon dioxide (CO 2 ) capture and storage (CCS) as a potential option for climate change mitigation. In addition to technology development, there is a need for modeling and assessment tools to evaluate and compare the cost and effectiveness of CCS methods. Analytical

296

Integrated science model for assessment of climate change  

SciTech Connect (OSTI)

Integrated assessment models are intended to represent processes that govern physical, ecological, economic and social systems. This report describes a scientific model relating emissions to global temperature and sea level. This model is intended to be one component of an integrated assessment model which is, of course, much more comprehensive. The model is able to reproduce past changes in CO{sub 2} concentration, global temperature, and sea level. The model is used to estimate the emissions rates required to lead to stabilization of CO{sub 2} at various levels. The model is also used to estimate global temperature rise, the rate of temperature change, and sea level rise driven by IPCC emissions scenarios. The emission of fossil fuel CO{sub 2} is modeled to have the largest long term effect on climate. Results do show the importance of expected changes of trace greenhouse gases other than CO{sub 2} in the near future. Because of the importance of these other trace gases, further work is recommended to more accurately estimate their effects.

Jain, A.K.; Wuebbles, D.J. [Lawrence Livermore National Lab., CA (United States); Kheshgi, H.S. [Exxon Research and Engineering Co., Annandale, NJ (United States)

1994-04-01T23:59:59.000Z

297

Model-based integrated management: applying autonomic systems engineering to network and systems management  

Science Journals Connector (OSTI)

We present a novel approach for integrated management of networks and information systems, based on the specification of executable behaviour models. A model processing plane is introduced, consisting of a number of processing units that together form ... Keywords: ASE, autonomic systems, autonomic systems engineering, behaviour modelling, information systems, management integration, model transformation, model-based integrated management, network management, systems management

Edzard Hofig; Peter H. Deussen

2011-12-01T23:59:59.000Z

298

Integration of the DAYCENT Biogeochemical Model within a Multi-Model Framework  

SciTech Connect (OSTI)

Agricultural residues are the largest near term source of cellulosic 13 biomass for bioenergy production, but removing agricultural residues sustainably 14 requires considering the critical roles that residues play in the agronomic system. 15 Determining sustainable removal rates for agricultural residues has received 16 significant attention and integrated modeling strategies have been built to evaluate 17 sustainable removal rates considering soil erosion and organic matter constraints. 18 However the current integrated model does not quantitatively assess soil carbon 19 and long term crop yields impacts of residue removal. Furthermore the current 20 integrated model does not evaluate the greenhouse gas impacts of residue 21 removal, specifically N2O and CO2 gas fluxes from the soil surface. The DAYCENT 22 model simulates several important processes for determining agroecosystem 23 performance. These processes include daily Nitrogen-gas flux, daily carbon dioxide 24 flux from soil respiration, soil organic carbon and nitrogen, net primary productivity, 25 and daily water and nitrate leaching. Each of these processes is an indicator of 26 sustainability when evaluating emerging cellulosic biomass production systems for 27 bioenergy. A potentially vulnerable cellulosic biomass resource is agricultural 28 residues. This paper presents the integration of the DAYCENT model with the 29 existing integration framework modeling tool to investigate additional environment 30 impacts of agricultural residue removal. The integrated model is extended to 31 facilitate two-way coupling between DAYCENT and the existing framework. The 32 extended integrated model is applied to investigate additional environmental 33 impacts from a recent sustainable agricultural residue removal dataset. The 34 integrated model with DAYCENT finds some differences in sustainable removal 35 rates compared to previous results for a case study county in Iowa. The extended 36 integrated model with DAYCENT also predicts that long term yields will decrease.

David Muth

2012-07-01T23:59:59.000Z

299

An integrative model of consumers' intentions to purchase travel online  

Science Journals Connector (OSTI)

Abstract Grounded in the Theory of Reasoned Action, the Theory of Planned Behaviour, the Technology Acceptance Model and on the Innovation Diffusions Theory, this study proposes and empirically tests an integrated model to explore which factors affect intentions to purchase travel online. Partial Least Squares Structural Equation Modelling was conducted to assess the hypotheses. The empirical results, obtained in a sample of 1732 Internet users, indicate that intentions to purchase travel online are mostly determined by attitude, compatibility and perceived risk. The theoretical contributions of this study and the practical implications are discussed and future research directions are detailed.

Suzanne Amaro; Paulo Duarte

2015-01-01T23:59:59.000Z

300

Do quantitative decadal forecasts from GCMs provide  

E-Print Network [OSTI]

' · Empirical models quantify our ability to predict without knowing the laws of physics · Climatology skill' model? 2. Dynamic climatology (DC) is a more appropriate benchmark for near- term (initialised) climate forecasts · A conditional climatology, initialised at launch and built from the historical archive

Stevenson, Paul

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Prediction versus Projection: How weather forecasting and  

E-Print Network [OSTI]

Prediction versus Projection: How weather forecasting and climate models differ. Aaron B. Wilson Context: Global http://data.giss.nasa.gov/ #12;Numerical Weather Prediction Collect Observations alters associated weather patterns. Models used to predict weather depend on the current observed state

Howat, Ian M.

302

Integrated reservoir characterization: Improvement in heterogeneities stochastic modelling by integration of additional external constraints  

SciTech Connect (OSTI)

The classical approach to construct reservoir models is to start with a fine scale geological model which is informed with petrophysical properties. Then scaling-up techniques allow to obtain a reservoir model which is compatible with the fluid flow simulators. Geostatistical modelling techniques are widely used to build the geological models before scaling-up. These methods provide equiprobable images of the area under investigation, which honor the well data, and which variability is the same than the variability computed from the data. At an appraisal phase, when few data are available, or when the wells are insufficient to describe all the heterogeneities and the behavior of the field, additional constraints are needed to obtain a more realistic geological model. For example, seismic data or stratigraphic models can provide average reservoir information with an excellent areal coverage, but with a poor vertical resolution. New advances in modelisation techniques allow now to integrate this type of additional external information in order to constrain the simulations. In particular, 2D or 3D seismic derived information grids, or sand-shale ratios maps coming from stratigraphic models can be used as external drifts to compute the geological image of the reservoir at the fine scale. Examples are presented to illustrate the use of these new tools, their impact on the final reservoir model, and their sensitivity to some key parameters.

Doligez, B.; Eschard, R. [Institut Francais du Petrole, Rueil Malmaison (France); Geffroy, F. [Centre de Geostatistique, Fontainebleau (France)] [and others

1997-08-01T23:59:59.000Z

303

An anticipatory integrated assessment of regional acidification: The RAINS-Asia model  

SciTech Connect (OSTI)

Across large parts of Asia, air pollution problems are becoming more and more evident. Rainfall in some areas, including China, Japan, and Thailand, has been measured to be 10 times more acidic than unpolluted rain. Increasing evidence of acidification damage to ecosystems such as surface waters, soils, and economically important crops, is beginning to appear. In addition, urban air quality in many areas of the region continues to decrease. Current economic forecasts predict continued rapid economic growth in the region, which will bring with it increasing emissions of air pollutants, especially sulfur. The total primary energy demand in Asia currently doubles every twelve years (as compared to a world average of every 28 years). Coal is expected to continue to be the dominant energy source, with coal demand projected to increase by 65 percent per year, a rate that outpaces regional economic growth. If current trends in economic development and energy use in Asia continue, emissions of sulfur dioxide, one of the key components in acid rain, will more than triple within the next 30 years. Many ecosystems will be unable to continue to absorb these increased levels of pollution without harmful effects, thus creating a potential danger for irreversible environmental damage in many areas. In view of the potential environmental consequences of projected growth in Asian energy consumption, emissions, and air pollution, the World Bank, together with the Asian Development Bank, have funded a project to develop and implement an integrated assessment model for the acid deposition phenomenon in Asia. The Regional Air Pollution INformation and Simulation model for Asia (RAINS-Asia) is a software tool to help decision makers assess and project future trends in emissions, transport, and deposition of air pollutants, and their potential environmental effects.

Amann, M. [International Institute for Applied Systems Analysis, Laxenburg (Austria); Carmichael, G.R. [Univ. of Iowa, Iowa City, IA (United States); Foell, W. [Resource Management Associates, Madison, WI (United States)] [and others

1996-12-31T23:59:59.000Z

304

Integrated Baseline Bystem (IBS) Version 1.03: Models guide  

SciTech Connect (OSTI)

The Integrated Baseline System)(IBS), operated by the Federal Emergency Management Agency (FEMA), is a system of computerized tools for emergency planning and analysis. This document is the models guide for the IBS and explains how to use the emergency related computer models. This document provides information for the experienced system user, and is the primary reference for the computer modeling software supplied with the system. It is designed for emergency managers and planners, and others familiar with the concepts of computer modeling. Although the IBS manual set covers basic and advanced operations, it is not a complete reference document set. Emergency situation modeling software in the IBS is supported by additional technical documents. Some of the other IBS software is commercial software for which more complete documentation is available. The IBS manuals reference such documentation where necessary.

Not Available

1993-01-01T23:59:59.000Z

305

Initial conditions estimation for improving forecast accuracy in exponential smoothing  

Science Journals Connector (OSTI)

In this paper we analyze the importance of initial conditions in exponential smoothing models on forecast errors and prediction intervals. We work with certain exponential smoothing models, namely Holt’s additive...

E. Vercher; A. Corberán-Vallet; J. V. Segura; J. D. Bermúdez

2012-07-01T23:59:59.000Z

306

Wind Speed Forecasting Using a Hybrid Neural-Evolutive Approach  

Science Journals Connector (OSTI)

The design of models for time series prediction has found a solid foundation on statistics. Recently, artificial neural networks have been a good choice as approximators to model and forecast time series. Designing a neural network that provides a good ...

Juan J. Flores; Roberto Loaeza; Héctor Rodríguez; Erasmo Cadenas

2009-11-01T23:59:59.000Z

307

Online short-term solar power forecasting  

SciTech Connect (OSTI)

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model. (author)

Bacher, Peder; Madsen, Henrik [Informatics and Mathematical Modelling, Richard Pedersens Plads, Technical University of Denmark, Building 321, DK-2800 Lyngby (Denmark); Nielsen, Henrik Aalborg [ENFOR A/S, Lyngsoe Alle 3, DK-2970 Hoersholm (Denmark)

2009-10-15T23:59:59.000Z

308

Integrable models and degenerate horizons in two-dimensional gravity  

E-Print Network [OSTI]

We analyse an integrable model of two-dimensional gravity which can be reduced to a pair of Liouville fields in conformal gauge. Its general solution represents a pair of ``mirror'' black holes with the same temperature. The ground state is a degenerate constant dilaton configuration similar to the Nariai solution of the Schwarzschild-de Sitter case. The existence of Birkhoff's theorem is then investigated in a more general context. We also point out some interesting features of the semiclassical theory of our model and the similarity with the behaviour of AdS$_2$ black holes.

Cruz, J; Navarro, D J; Navarro-Salas, J

2000-01-01T23:59:59.000Z

309

Integrable models and degenerate horizons in two-dimensional gravity  

Science Journals Connector (OSTI)

We analyze an integrable model of two-dimensional gravity which can be reduced to a pair of Liouville fields in the conformal gauge. Its general solution represents a pair of “mirror” black holes with the same temperature. The ground state is a degenerate constant dilaton configuration similar to the Nariai solution of the Schwarzschild–de Sitter case. The existence of ?=const solutions and their relation to the solution given by the 2D Birkhoff theorem is then investigated in a more general context. We also point out some interesting features of the semiclassical theory of our model and the similarity with the behavior of AdS2 black holes.

J. Cruz; A. Fabbri; D. J. Navarro; J. Navarro-Salas

1999-12-20T23:59:59.000Z

310

Integrable models and degenerate horizons in two-dimensional gravity  

E-Print Network [OSTI]

We analyse an integrable model of two-dimensional gravity which can be reduced to a pair of Liouville fields in conformal gauge. Its general solution represents a pair of ``mirror'' black holes with the same temperature. The ground state is a degenerate constant dilaton configuration similar to the Nariai solution of the Schwarzschild-de Sitter case. The existence of $\\phi=const.$ solutions and their relation with the solution given by the 2D Birkhoff's theorem is then investigated in a more general context. We also point out some interesting features of the semiclassical theory of our model and the similarity with the behaviour of AdS$_2$ black holes.

J. Cruz; A. Fabbri; D. J. Navarro; J. Navarro-Salas

1999-06-24T23:59:59.000Z

311

MIT Integrated Global System Model (IGSM) Version 2: Model Description and Baseline Evaluation  

E-Print Network [OSTI]

The MIT Integrated Global System Model (IGSM) is designed for analyzing the global environmental changes that may result from anthropogenic causes, quantifying the uncertainties associated with the projected changes, and ...

Sokolov, Andrei P.

312

Integration of Nonlinear CDU Models in RefineryCDU Models in Refinery  

E-Print Network [OSTI]

planning models Optimizing refinery operation C d l ti Crude selection Maximizing profit; minimizing costIntegration of Nonlinear CDU Models in RefineryCDU Models in Refinery Planning Optimization Carnegie Mellon University EWO Meeting ­ March 2011 1 #12;I t d tiIntroduction Refinery production

Grossmann, Ignacio E.

313

Modeling fabrication of nuclear components: An integrative approach  

SciTech Connect (OSTI)

Reduction of the nuclear weapons stockpile and the general downsizing of the nuclear weapons complex has presented challenges for Los Alamos. One is to design an optimized fabrication facility to manufacture nuclear weapon primary components in an environment of intense regulation and shrinking budgets. This dissertation presents an integrative two-stage approach to modeling the casting operation for fabrication of nuclear weapon primary components. The first stage optimizes personnel radiation exposure for the casting operation layout by modeling the operation as a facility layout problem formulated as a quadratic assignment problem. The solution procedure uses an evolutionary heuristic technique. The best solutions to the layout problem are used as input to the second stage - a simulation model that assesses the impact of competing layouts on operational performance. The focus of the simulation model is to determine the layout that minimizes personnel radiation exposures and nuclear material movement, and maximizes the utilization of capacity for finished units.

Hench, K.W.

1996-08-01T23:59:59.000Z

314

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 3 AUGUST 16, 2012  

E-Print Network [OSTI]

there is significant uncertainty in its future intensity, the current forecast is for a slowly strengthening TC which, 3) forecast output from global models, 4) the current and projected state of the Madden with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all

Gray, William

315

Lessons from Deploying NLG Technology for Marine Weather Forecast Text Generation  

E-Print Network [OSTI]

model along with other sources of weather data such as satellite pictures and their own forecastingLessons from Deploying NLG Technology for Marine Weather Forecast Text Generation Somayajulu G Language Generation (NLG) system that produces textual weather forecasts for offshore oilrigs from

Sripada, Yaji

316

Ensemble-based air quality forecasts: A multimodel approach applied to ozone  

E-Print Network [OSTI]

Ensemble-based air quality forecasts: A multimodel approach applied to ozone Vivien Mallet1., and B. Sportisse (2006), Ensemble-based air quality forecasts: A multimodel approach applied to ozone, J, the uncertainty in chem- istry transport models is a major limitation of air quality forecasting. The source

Boyer, Edmond

317

Consensus Coal Production Forecast for  

E-Print Network [OSTI]

Rate Forecasts 19 5. EIA Forecast: Regional Coal Production 22 6. Wood Mackenzie Forecast: W.V. Steam to data currently published by the Energy Information Administration (EIA), coal production in the state in this report calls for state production to decline by 11.3 percent in 2009 to 140.2 million tons. During

Mohaghegh, Shahab

318

Improving the forecasting function for a Credit Hire operator in the UK  

Science Journals Connector (OSTI)

This study aims to test on the predictability of Credit Hire services for the automobile and insurance industry. A relatively sophisticated time series forecasting procedure, which conducts a competition among exponential smoothing models, is employed to forecast demand for a leading UK Credit Hire operator (CHO). The generated forecasts are compared against the Naive method, resulting that demand for CHO services is indeed extremely hard to forecast, as the underlying variable is the number of road accidents – a truly stochastic variable.

Nicolas D. Savio; K. Nikolopoulos; Konstantinos Bozos

2009-01-01T23:59:59.000Z

319

Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe  

Science Journals Connector (OSTI)

Abstract This article combines and discusses three independent validations of global horizontal irradiance (GHI) multi-day forecast models that were conducted in the US, Canada and Europe. All forecast models are based directly or indirectly on numerical weather prediction (NWP). Two models are common to the three validation efforts – the ECMWF global model and the GFS-driven WRF mesoscale model – and allow general observations: (1) the GFS-based WRF- model forecasts do not perform as well as global forecast-based approaches such as ECMWF and (2) the simple averaging of models’ output tends to perform better than individual models.

Richard Perez; Elke Lorenz; Sophie Pelland; Mark Beauharnois; Glenn Van Knowe; Karl Hemker Jr.; Detlev Heinemann; Jan Remund; Stefan C. Müller; Wolfgang Traunmüller; Gerald Steinmauer; David Pozo; Jose A. Ruiz-Arias; Vicente Lara-Fanego; Lourdes Ramirez-Santigosa; Martin Gaston-Romero; Luis M. Pomares

2013-01-01T23:59:59.000Z

320

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Table 2. Total Energy Consumption, Actual vs. Forecasts Table 3. Total Petroleum Consumption, Actual vs. Forecasts Table 4. Total Natural Gas Consumption, Actual vs. Forecasts Table 5. Total Coal Consumption, Actual vs. Forecasts Table 6. Total Electricity Sales, Actual vs. Forecasts Table 7. Crude Oil Production, Actual vs. Forecasts Table 8. Natural Gas Production, Actual vs. Forecasts Table 9. Coal Production, Actual vs. Forecasts Table 10. Net Petroleum Imports, Actual vs. Forecasts Table 11. Net Natural Gas Imports, Actual vs. Forecasts Table 12. Net Coal Exports, Actual vs. Forecasts Table 13. World Oil Prices, Actual vs. Forecasts Table 14. Natural Gas Wellhead Prices, Actual vs. Forecasts Table 15. Coal Prices to Electric Utilities, Actual vs. Forecasts

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Lifting metamodels to ontologies: a step to the semantic integration of modeling languages  

Science Journals Connector (OSTI)

The use of different modeling languages in software development makes their integration a must. Most existing integration approaches are metamodel-based with these metamodels representing both an abstract syntax of the corresponding modeling language ...

Gerti Kappel; Elisabeth Kapsammer; Horst Kargl; Gerhard Kramler; Thomas Reiter; Werner Retschitzegger; Wieland Schwinger; Manuel Wimmer

2006-10-01T23:59:59.000Z

322

On Sequential Probability Forecasting  

E-Print Network [OSTI]

at the same time. [Probability, Statistics and Truth, MacMillan 1957. page 11] ... the collective "denotes a collective wherein the attribute of the single event is the number of points thrown. [Probability, StatisticsOn Sequential Probability Forecasting David A. Bessler 1 David A. Bessler Texas A&M University

McCarl, Bruce A.

323

Process modeling for the Integrated Thermal Treatment System (ITTS) study  

SciTech Connect (OSTI)

This report describes the process modeling done in support of the integrated thermal treatment system (ITTS) study, Phases 1 and 2. ITTS consists of an integrated systems engineering approach for uniform comparison of widely varying thermal treatment technologies proposed for treatment of the contact-handled mixed low-level wastes (MLLW) currently stored in the U.S. Department of Energy complex. In the overall study, 19 systems were evaluated. Preconceptual designs were developed that included all of the various subsystems necessary for a complete installation, from waste receiving through to primary and secondary stabilization and disposal of the processed wastes. Each system included the necessary auxiliary treatment subsystems so that all of the waste categories in the complex were fully processed. The objective of the modeling task was to perform mass and energy balances of the major material components in each system. Modeling of trace materials, such as pollutants and radioactive isotopes, were beyond the present scope. The modeling of the main and secondary thermal treatment, air pollution control, and metal melting subsystems was done using the ASPEN PLUS process simulation code, Version 9.1-3. These results were combined with calculations for the remainder of the subsystems to achieve the final results, which included offgas volumes, and mass and volume waste reduction ratios.

Liebelt, K.H.; Brown, B.W.; Quapp, W.J.

1995-09-01T23:59:59.000Z

324

Methods for Developing Emissions Scenarios for Integrated Assessment Models  

SciTech Connect (OSTI)

The overall objective of this research was to contribute data and methods to support the future development of new emissions scenarios for integrated assessment of climate change. Specifically, this research had two main objectives: 1. Use historical data on economic growth and energy efficiency changes, and develop probability density functions (PDFs) for the appropriate parameters for two or three commonly used integrated assessment models. 2. Using the parameter distributions developed through the first task and previous work, we will develop methods of designing multi-gas emission scenarios that usefully span the joint uncertainty space in a small number of scenarios. Results on the autonomous energy efficiency improvement (AEEI) parameter are summarized, an uncertainty analysis of elasticities of substitution is described, and the probabilistic emissions scenario approach is presented.

Prinn, Ronald [MIT; Webster, Mort [MIT

2007-08-20T23:59:59.000Z

325

Data Integration for the Generation of High Resolution Reservoir Models  

SciTech Connect (OSTI)

The goal of this three-year project was to develop a theoretical basis and practical technology for the integration of geologic, production and time-lapse seismic data in a way that makes best use of the information for reservoir description and reservoir performance predictions. The methodology and practical tools for data integration that were developed in this research project have been incorporated into computational algorithms that are feasible for large scale reservoir simulation models. As the integration of production and seismic data require calibrating geological/geostatistical models to these data sets, the main computational tool is an automatic history matching algorithm. The following specific goals were accomplished during this research. (1) We developed algorithms for calibrating the location of the boundaries of geologic facies and the distribution of rock properties so that production and time-lapse seismic data are honored. (2) We developed and implemented specific procedures for conditioning reservoir models to time-lapse seismic data. (3) We developed and implemented algorithms for the characterization of measurement errors which are needed to determine the relative weights of data when conditioning reservoir models to production and time-lapse seismic data by automatic history matching. (4) We developed and implemented algorithms for the adjustment of relative permeability curves during the history matching process. (5) We developed algorithms for production optimization which accounts for geological uncertainty within the context of closed-loop reservoir management. (6) To ensure the research results will lead to practical public tools for independent oil companies, as part of the project we built a graphical user interface for the reservoir simulator and history matching software using Visual Basic.

Albert Reynolds; Dean Oliver; Gaoming Li; Yong Zhao; Chaohui Che; Kai Zhang; Yannong Dong; Chinedu Abgalaka; Mei Han

2009-01-07T23:59:59.000Z

326

Storm-in-a-Box Forecasting  

Science Journals Connector (OSTI)

...But the WRF has no immediate...being tuned to local conditions...temperatures and winds with altitude...resulting WRF forecasts...captured the local sea-breeze winds better...spread the local operation of mesoscale...to be the WRF model now...

Richard A. Kerr

2004-05-14T23:59:59.000Z

327

Can agent-based models forecast spot prices in electricity markets? Evidence from the New Zealand electricity market  

Science Journals Connector (OSTI)

Abstract Modelling price formation in electricity markets is a notoriously difficult process, due to physical constraints on electricity generation and transmission, and the potential for market power. This difficulty has inspired the recent development of bottom-up agent-based algorithmic learning models of electricity markets. While these have proven quite successful in small models, few authors have attempted any validation of their model against real-world data in a more realistic model. In this paper we develop the SWEM model, where we take one of the most promising algorithms from the literature, a modified version of the Roth and Erev algorithm, and apply it to a 19-node simplification of the New Zealand electricity market. Once key variables such as water storage are accounted for, we show that our model can closely mimic short-run (weekly) electricity prices at these 19 nodes, given fundamental inputs such as fuel costs, network data, and demand. We show that agents in SWEM are able to manipulate market power when a line outage makes them an effective monopolist in the market. SWEM has already been applied to a wide variety of policy applications in the New Zealand market.22 This research was partly funded by a University of Auckland FDRF Grant #9554/3627082. The authors would like thank Andy Philpott, Golbon Zakeri, Anthony Downward, an anonymous referee, and participants at the EPOC Winter Workshop 2010 for their helpful comments.

David Young; Stephen Poletti; Oliver Browne

2014-01-01T23:59:59.000Z

328

Integrated thermal-microstructure model to predict the property gradients in resistance spot steel welds  

SciTech Connect (OSTI)

An integrated model approach was proposed for relating resistance welding parameters to weldment properties. An existing microstructure model was used to determine the microstructural and property gradients in resistance spot welds of plain carbon steel. The effect of these gradients on the weld integrity was evaluated with finite element analysis. Further modifications to this integrated thermal-microstructure model are discussed.

Babu, S.S.; Riemer, B.W.; Santella, M.L. [Oak Ridge National Lab., TN (United States); Feng, Z. [Edison Welding Inst., Columbus, OH (United States)

1998-11-01T23:59:59.000Z

329

Examining emissions policy issues with an integrated assessment model  

SciTech Connect (OSTI)

In the policy analysis process of asking ``What if'' questions, there is considerable advantage in the analyst being able to address the questions directly rather than sending the questions to scientists in particular disciplines and awaiting answers. Obviously the former option is likely to produce speedier results than the latter; in addition, the questions can be easily modified as the issues change or become more focused. The primary potential shortcoming of an analyst addressing questions that may be beyond his or her particular expertise is that the policy analyst may not understand the limitations of the analysis. Here the author briefly describes a peer-reviewed integrated assessment model that can be exercised within minutes in a desktop environment, discuss some of the advantages and limitations of the approach, and exercise portions of the model to compare with observations. Because of the nature of the conference at which this paper is being presented, the discussion focuses on the air pollution modeling components of the integrated assessment.

Shannon, J. D.

1999-10-21T23:59:59.000Z

330

Simplified risk model support for environmental management integration  

SciTech Connect (OSTI)

This paper summarizes the process and results of human health risk assessments of the US Department of Energy (DOE) complex-wide programs for high-level waste, transuranic waste, low-level, mixed low-level waste, and spent nuclear fuel. The DOE baseline programs and alternatives for these five material types were characterized by disposition maps (material flow diagrams) and supporting information in the May 1997 report `A Contractor Report to the Department of Energy on Environmental Baseline Programs and Integration Opportunities` (Discussion Draft). Risk analyses were performed using the Simplified Risk Model (SRM), developed to support DOE Environmental Management Integration studies. The SRM risk analyses consistently and comprehensively cover the life cycle programs for the five material types, from initial storage through final disposition. Risk results are presented at several levels: DOE complex-wide, material type program, individual DOE sites, and DOE site activities. The detailed risk results are documented in the February 1998 report `Human Health Risk Comparisons for Environmental Management Baseline Programs and Integration Opportunities` (Discussion Draft).

Eide, S.A.; Jones, J.L.; Wierman, T.E.

1998-03-01T23:59:59.000Z

331

Ontologies for the Integration of Air Quality Models and 3D City Models  

E-Print Network [OSTI]

-city densification may limit air pollution, carbon emissions, and energy use through reduced transportation of the most important environmental problems is air pollution, mostly induced by vehicle traffic1 Ontologies for the Integration of Air Quality Models and 3D City Models Claudine Metral Institut

Genève, Université de

332

Integrating model-in-the-loop simulations to model-driven development in industrial control  

Science Journals Connector (OSTI)

Software applications are becoming increasingly important in automation and control systems. This has forced control system vendors and integrators to pursue new, more effective software development practices. One of the promising research paths has ... Keywords: Model-driven development, automation and control, model-in-the-loop, simulations

Timo Vepsäläinen, Seppo Kuikka

2014-12-01T23:59:59.000Z

333

Coal production forecast and low carbon policies in China  

Science Journals Connector (OSTI)

With rapid economic growth and industrial expansion, China consumes more coal than any other nation. Therefore, it is particularly crucial to forecast China's coal production to help managers make strategic decisions concerning China's policies intended to reduce carbon emissions and concerning the country's future needs for domestic and imported coal. Such decisions, which must consider results from forecasts, will have important national and international effects. This article proposes three improved forecasting models based on grey systems theory: the Discrete Grey Model (DGM), the Rolling DGM (RDGM), and the p value RDGM. We use the statistical data of coal production in China from 1949 to 2005 to validate the effectiveness of these improved models to forecast the data from 2006 to 2010. The performance of the models demonstrates that the p value RDGM has the best forecasting behaviour over this historical time period. Furthermore, this paper forecasts coal production from 2011 to 2015 and suggests some policies for reducing carbon and other emissions that accompany the rise in forecasted coal production.

Jianzhou Wang; Yao Dong; Jie Wu; Ren Mu; He Jiang

2011-01-01T23:59:59.000Z

334

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications  

E-Print Network [OSTI]

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange­based surface evapotranspiration

Niyogi, Dev

335

Modeling renewable energy resources in integrated resource planning  

SciTech Connect (OSTI)

Including renewable energy resources in integrated resource planning (IRP) requires that utility planning models properly consider the relevant attributes of the different renewable resources in addition to conventional supply-side and demand-side options. Otherwise, a utility`s resource plan is unlikely to have an appropriate balance of the various resource options. The current trend toward regulatory set-asides for renewable resources is motivated in part by the perception that the capabilities of current utility planning models are inadequate with regard to renewable resources. Adequate modeling capabilities and utility planning practices are a necessary prerequisite to the long-term penetration of renewable resources into the electric utility industry`s resource mix. This report presents a review of utility planning models conducted for the National Renewable Energy Laboratory (NREL). The review examines the capabilities of utility planning models to address key issues in the choice between renewable resources and other options. The purpose of this review is to provide a basis for identifying high priority areas for advancing the state of the art.

Logan, D.; Neil, C.; Taylor, A. [RCG/Hagler, Bailly, Inc., Boulder, CO (United States)

1994-06-01T23:59:59.000Z

336

2007 National Hurricane Center Forecast Verification Report James L. Franklin  

E-Print Network [OSTI]

storms 17 4. Genesis Forecasts 17 5. Summary and Concluding Remarks 18 a. Atlantic Summary 18 statistical models, provided the best intensity guidance at each time period. The 2007 season marked the first

337

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network [OSTI]

......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

338

Evolutionary Optimization of an Ice Accretion Forecasting System  

Science Journals Connector (OSTI)

The ability to model and forecast accretion of ice on structures is very important for many industrial sectors. For example, studies conducted by the power transmission industry indicate that the majority of failures are caused by icing on ...

Pawel Pytlak; Petr Musilek; Edward Lozowski; Dan Arnold

2010-07-01T23:59:59.000Z

339

Diagnosing the Origin of Extended-Range Forecast Errors  

Science Journals Connector (OSTI)

Experiments with the ECMWF model are carried out to study the influence that a correct representation of the lower boundary conditions, the tropical atmosphere, and the Northern Hemisphere stratosphere would have on extended-range forecast skill ...

T. Jung; M. J. Miller; T. N. Palmer

2010-06-01T23:59:59.000Z

340

OpenEI Community - energy data + forecasting  

Open Energy Info (EERE)

FRED FRED http://en.openei.org/community/group/fred Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. energy data + forecasting Fri, 22 Jun 2012 15:30:20 +0000 Dbrodt 34

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Project Modelling To utilise the types of integrated design system that can be described with the modelling and  

E-Print Network [OSTI]

Chapter 7 Project Modelling To utilise the types of integrated design system that can be described the tasks and people involved in the projects in which the integrated system is used. This level of modelling enables an integrated design system to be customised for use in a specific project. Project

Goodman, James R.

342

Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS  

E-Print Network [OSTI]

of the Department of Energy's Office of Industrial Technologies, EIA extracted energy use infonnation from the Annual Energy Outlook (AEO) - 2000 (8) for each of the seven # The Pacific Northwest National Laboratory is operated by Battelle Memorial Institute...-6, 2000 NEMS The NEMS industrial module is the official forecasting model for EIA and thus the Department of Energy. For this reason, the energy prices and output forecasts used to drive the ITEMS model were taken from EIA's AEO 2000. Understanding...

Roop, J. M.; Dahowski, R. T

343

Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory  

Gasoline and Diesel Fuel Update (EIA)

Forecasting Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels MICHAEL YE, ∗ JOHN ZYREN, ∗∗ AND JOANNE SHORE ∗∗ Abstract This paper presents a short-term monthly forecasting model of West Texas Intermedi- ate crude oil spot price using OECD petroleum inventory levels. Theoretically, petroleum inventory levels are a measure of the balance, or imbalance, between petroleum production and demand, and thus provide a good market barometer of crude oil price change. Based on an understanding of petroleum market fundamentals and observed market behavior during the post-Gulf War period, the model was developed with the objectives of being both simple and practical, with required data readily available. As a result, the model is useful to industry and government decision-makers in forecasting price and investigat- ing the impacts of changes on price, should inventories,

344

Exponential smoothing with covariates applied to electricity demand forecast  

Science Journals Connector (OSTI)

Exponential smoothing methods are widely used as forecasting techniques in industry and business. Their usual formulation, however, does not allow covariates to be used for introducing extra information into the forecasting process. In this paper, we analyse an extension of the exponential smoothing formulation that allows the use of covariates and the joint estimation of all the unknowns in the model, which improves the forecasting results. The whole procedure is detailed with a real example on forecasting the daily demand for electricity in Spain. The time series of daily electricity demand contains two seasonal patterns: here the within-week seasonal cycle is modelled as usual in exponential smoothing, while the within-year cycle is modelled using covariates, specifically two harmonic explanatory variables. Calendar effects, such as national and local holidays and vacation periods, are also introduced using covariates. [Received 28 September 2010; Revised 6 March 2011, 2 October 2011; Accepted 16 October 2011

José D. Bermúdez

2013-01-01T23:59:59.000Z

345

Solar Wind Forecasting with Coronal Holes  

E-Print Network [OSTI]

An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

S. Robbins; C. J. Henney; J. W. Harvey

2007-01-09T23:59:59.000Z

346

Electrical conductivity of continental lithospheric mantle from integrated geophysical and petrological modeling  

E-Print Network [OSTI]

Electrical conductivity of continental lithospheric mantle from integrated geophysical; published 11 October 2011. [1] The electrical conductivity of mantle minerals is highly sensitive, and compositional variations. The bulk electrical conductivity model has been integrated into the software package

Jones, Alan G.

347

Price forecasting for notebook computers.  

E-Print Network [OSTI]

??This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a… (more)

Rutherford, Derek Paul

2012-01-01T23:59:59.000Z

348

Ensemble Forecasts and their Verification  

E-Print Network [OSTI]

· Ensemble forecast verification ­ Performance metrics: Brier Score, CRPSS · New concepts and developments of weather Sources: Insufficient spatial resolution, truncation errors in the dynamical equations

Maryland at College Park, University of

349

UNCERTAINTY IN THE GLOBAL FORECAST SYSTEM  

SciTech Connect (OSTI)

We validated one year of Global Forecast System (GFS) predictions of surface meteorological variables (wind speed, air temperature, dewpoint temperature, air pressure) over the entire planet for forecasts extending from zero hours into the future (an analysis) to 36 hours. Approximately 12,000 surface stations world-wide were included in this analysis. Root-Mean-Square- Errors (RMSE) increased as the forecast period increased from zero to 36 hours, but the initial RMSE were almost as large as the 36 hour forecast RMSE for all variables. Typical RMSE were 3 C for air temperature, 2-3mb for sea-level pressure, 3.5 C for dewpoint temperature and 2.5 m/s for wind speed. Approximately 20-40% of the GFS errors can be attributed to a lack of resolution of local features. We attribute the large initial RMSE for the zero hour forecasts to the inability of the GFS to resolve local terrain features that often dominate local weather conditions, e.g., mountain- valley circulations and sea and land breezes. Since the horizontal resolution of the GFS (about 1{sup o} of latitude and longitude) prevents it from simulating these locally-driven circulations, its performance will not improve until model resolution increases by a factor of 10 or more (from about 100 km to less than 10 km). Since this will not happen in the near future, an alternative for the near term to improve surface weather analyses and predictions for specific points in space and time would be implementation of a high-resolution, limited-area mesoscale atmospheric prediction model in regions of interest.

Werth, D.; Garrett, A.

2009-04-15T23:59:59.000Z

350

Integrated Numerical Modeling Process for Evaluating Automobile Climate Control Systems  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

FCC-70 FCC-70 Integrated Numerical Modeling Process for Evaluating Automobile Climate Control Systems John Rugh National Renewable Energy Laboratory Copyright © 2002 Society of Automotive Engineers, Inc. ABSTRACT The air-conditioning (A/C) system compressor load can significantly impact the fuel economy and tailpipe emissions of conventional and hybrid electric automobiles. With the increasing emphasis on fuel economy, it is clear that the A/C compressor load needs to be reduced. In order to accomplish this goal, more efficient climate control delivery systems and reduced peak soak temperatures will be necessary to reduce the impact of vehicle A/C systems on fuel economy and tailpipe emissions. Good analytical techniques are important in identifying promising concepts. The goal at

351

Model Predictive Control of Integrated Gasification Combined Cycle Power Plants  

SciTech Connect (OSTI)

The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

B. Wayne Bequette; Priyadarshi Mahapatra

2010-08-31T23:59:59.000Z

352

Probabilistic manpower forecasting  

E-Print Network [OSTI]

- ing E. Results- Probabilistic Forecasting . 26 27 Z8 29 31 35 36 38 39 IV. CONCLUSIONS. V. GLOSSARY 42 44 APPENDICES REFERENCES 50 70 LIST OF TABLES Table Page Outline of Job-Probability Matrix Job-Probability Matrix. Possible... Outcomes of Job A Possible Outcomes of Jobs A and B 10 Possible Outcomes of Jobs A, B and C II LIST GF FIGURES Figure Page Binary Representation of Numbers 0 Through 7 12 First Cumulative Probability Table 14 3. Graph of Cumulative Probability vs...

Koonce, James Fitzhugh

1966-01-01T23:59:59.000Z

353

ForReviewers Integrating Theoretical Components: A Graphical Model for  

E-Print Network [OSTI]

formulating a hypothesis, four avenues of194 integration (Integration Routes � IR, dashed lines in Figure 1 to form a new hypothesis on the effects of predation risk on200 disease transmission of the host while foraging.221 We do not include integration routes between identical components (e.g., laws

Prather, Chelse M.

354

Mid-term electricity market clearing price forecasting: A hybrid LSSVM and ARMAX approach  

Science Journals Connector (OSTI)

Abstract A hybrid mid-term electricity market clearing price (MCP) forecasting model combining both least squares support vector machine (LSSVM) and auto-regressive moving average with external input (ARMAX) modules is presented in this paper. Mid-term electricity MCP forecasting has become essential for resources reallocation, maintenance scheduling, bilateral contracting, budgeting and planning purposes. Currently, there are many techniques available for short-term electricity market clearing price (MCP) forecasting, but very little has been done in the area of mid-term electricity MCP forecasting. PJM interconnection data have been utilized to illustrate the proposed model with numerical examples. The proposed hybrid model showed improved forecasting accuracy compared to a forecasting model using a single LSSVM.

Xing Yan; Nurul A. Chowdhury

2013-01-01T23:59:59.000Z

355

A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China  

SciTech Connect (OSTI)

Highlights: ? We propose a hybrid model that combines seasonal SARIMA model and grey system theory. ? The model is robust at multiple time scales with the anticipated accuracy. ? At month-scale, the SARIMA model shows good representation for monthly MSW generation. ? At medium-term time scale, grey relational analysis could yield the MSW generation. ? At long-term time scale, GM (1, 1) provides a basic scenario of MSW generation. - Abstract: Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 – 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 – 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term.

Xu, Lilai, E-mail: llxu@iue.ac.cn [Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen 361021 (China); Xiamen Key Lab of Urban Metabolism, Xiamen 361021 (China); Gao, Peiqing, E-mail: peiqing15@yahoo.com.cn [Xiamen City Appearance and Environmental Sanitation Management Office, 51 Hexiangxi Road, Xiamen 361004 (China); Cui, Shenghui, E-mail: shcui@iue.ac.cn [Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen 361021 (China); Xiamen Key Lab of Urban Metabolism, Xiamen 361021 (China); Liu, Chun, E-mail: xmhwlc@yahoo.com.cn [Xiamen City Appearance and Environmental Sanitation Management Office, 51 Hexiangxi Road, Xiamen 361004 (China)

2013-06-15T23:59:59.000Z

356

Integrated Modeling and Design of Lightweight, Active Mirrors for Launch Survival and On-Orbit  

E-Print Network [OSTI]

Integrated Modeling and Design of Lightweight, Active Mirrors for Launch Survival and On-Orbit Performance Lucy E. Cohan and David W. Miller June 2010 SSL# 2-10 #12;#12;Integrated Modeling and Design-based design and evolutionary models to guide the technology development program. This methodology is applied

357

A FLEXIBLE, MODULAR APPROACH TO INTEGRATED SPACE EXPLORATION CAMPAIGN LOGISTICS MODELING, SIMULATION, AND ANALYSIS  

E-Print Network [OSTI]

A FLEXIBLE, MODULAR APPROACH TO INTEGRATED SPACE EXPLORATION CAMPAIGN LOGISTICS MODELING Students #12;2 A FLEXIBLE, MODULAR APPROACH TO INTEGRATED SPACE EXPLORATION CAMPAIGN LOGISTICS MODELING in Aeronautics and Astronautics #12;3 Abstract A space logistics modeling framework to support space exploration

de Weck, Olivier L.

358

A framework for fast 3D solid model exchange in integrated design environment  

Science Journals Connector (OSTI)

Exchanging 3D solid models across engineering applications has become increasingly important to integrated design environments (IDEs). However, transferring models among distributed locations via computer networks usually consumes large amounts of network ... Keywords: Incremental editing, Integrated design environment, Progressive streaming, Solid model

Di Wu; Radha Sarma

2005-04-01T23:59:59.000Z

359

Project Profile: Forecasting and Influencing Technological Progress...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Logos of the University of...

360

Forecasting with adaptive extended exponential smoothing  

Science Journals Connector (OSTI)

Much of product level forecasting is based upon time series techniques. However, traditional time series forecasting techniques have offered either smoothing constant adaptability or consideration of various t...

John T. Mentzer Ph.D.

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Electricity price forecasting in a grid environment.  

E-Print Network [OSTI]

??Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. Market participants rely on price forecasts to decide their bidding strategies, allocate… (more)

Li, Guang, 1974-

2007-01-01T23:59:59.000Z

362

Energy Department Forecasts Geothermal Achievements in 2015 ...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Forecasts Geothermal Achievements in 2015 Energy Department Forecasts Geothermal Achievements in 2015 The 40th annual Stanford Geothermal Workshop in January featured speakers in...

363

timber quality Modelling and forecasting  

E-Print Network [OSTI]

facilities match the more traditional requirements of timber production. As this policy evolves will also incorporate carbon and energy budgeting modules to assist in the cost­benefit analysis of forest aimed at the optimisation of sustainable management, the provision of renewable resources

364

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Title of Paper Annual Energy Outlook Forecast Evaluation Title of Paper Annual Energy Outlook Forecast Evaluation by Susan H. Holte OIAF has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Natural gas has generally been the fuel with the least accurate forecasts of consumption, production, and prices. Natural gas was the last fossil fuel to be deregulated following the strong regulation of energy markets in the 1970s and early 1980s. Even after deregulation, the behavior

365

Improving Energy Use Forecast for Campus Micro-grids using Indirect Indicators Department of Computer Science  

E-Print Network [OSTI]

.32%, and a reduction in error from baseline models by up to 53%. Keywords-energy forecast models; energy informatics I that physically char- acterize a building, or are based on measured building performance data. Smart meters have analysis and machine learning methods can be used to mine sensor data and extract forecast models

Prasanna, Viktor K.

366

Gridded Operational Consensus Forecasts of 2-m Temperature over Australia CHERMELLE ENGEL  

E-Print Network [OSTI]

-resolution grid. Local and in- ternational numerical weather prediction model inputs are found to have coarse by numerical weather prediction (NWP) model forecasts. As NWP models improve, public weather forecasting University of Melbourne, Melbourne, Victoria, Australia ELIZABETH E. EBERT Centre for Australia Weather

Ebert, Beth

367

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height ADAM J. DEPPE AND WILLIAM A. GALLUS JR.  

E-Print Network [OSTI]

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height ADAM J. DEPPE AND WILLIAM A in wind speed forecasts at a typical wind turbine hub height (80 m). An ensemble consisting of WRF model ensemble members for forecasting wind speed. A second configuration using three random perturbations

McCalley, James D.

368

Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts  

E-Print Network [OSTI]

Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts Antonio that the inherent variability in wind power generation and the related difficulty in predicting future generation profiles, raise major challenges to wind power integration into the electricity grid. In this work we study

Giannitrapani, Antonello

369

Model-Based Testing for the Second Generation of Integrated Modular Avionics Christof Efkemann, Jan Peleska  

E-Print Network [OSTI]

activities regarding automated testing of Integrated Modular Avionics controllers in the European research, specialised electronics devices, many of them with cus- tom interfaces. In the Integrated Modular AvionicsModel-Based Testing for the Second Generation of Integrated Modular Avionics Christof Efkemann, Jan

Peleska, Jan - Fachbereich 3

370

Forecasting in Fuzzy Time Series by an Extension of Simple Exponential Smoothing  

Science Journals Connector (OSTI)

Time Series was introduced to improve the forecasting made by statistical methods in vague or imprecise data and in time series with few samples available. However, the integration of these concepts is a little e...

Fábio José Justo dos Santos…

2014-01-01T23:59:59.000Z

371

Analysis of Mesoscale Model Data for Wind Integration (Poster)  

SciTech Connect (OSTI)

Supports examination of implications of national 20% wind vision, and provides input to integration and transmission studies for operational impact of large penetrations of wind on the grid.

Schwartz, M.; Elliott, D.; Lew, D.; Corbus, D.; Scott, G.; Haymes, S.; Wan, Y. H.

2009-05-01T23:59:59.000Z

372

Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) | Open  

Open Energy Info (EERE)

Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Jump to: navigation, search LEDSGP green logo.png FIND MORE DIA TOOLS This tool is part of the Development Impacts Assessment (DIA) Toolkit from the LEDS Global Partnership. Tool Summary LAUNCH TOOL Name: Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Agency/Company /Organization: Energy Sector Management Assistance Program of the World Bank Sector: Energy Focus Area: Non-renewable Energy Topics: Baseline projection, Co-benefits assessment, GHG inventory Resource Type: Software/modeling tools User Interface: Spreadsheet Complexity/Ease of Use: Simple Website: www.esmap.org/esmap/EFFECT Cost: Free Equivalent URI: www.esmap.org/esmap/EFFECT Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Screenshot

373

Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin  

SciTech Connect (OSTI)

A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatial scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.

Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.; Buizza, Roberto; Schaake, John

2011-08-15T23:59:59.000Z

374

Weather-based forecasts of California crop yields  

SciTech Connect (OSTI)

Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over the 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.

Lobell, D B; Cahill, K N; Field, C B

2005-09-26T23:59:59.000Z

375

Wave height forecasting in Dayyer, the Persian Gulf  

Science Journals Connector (OSTI)

Forecasting of wave parameters is necessary for many marine and coastal operations. Different forecasting methodologies have been developed using the wind and wave characteristics. In this paper, artificial neural network (ANN) as a robust data learning method is used to forecast the wave height for the next 3, 6, 12 and 24 h in the Persian Gulf. To determine the effective parameters, different models with various combinations of input parameters were considered. Parameters such as wind speed, direction and wave height of the previous 3 h, were found to be the best inputs. Furthermore, using the difference between wave and wind directions showed better performance. The results also indicated that if only the wind parameters are used as model inputs the accuracy of the forecasting increases as the time horizon increases up to 6 h. This can be due to the lower influence of previous wave heights on larger lead time forecasting and the existing lag between the wind and wave growth. It was also found that in short lead times, the forecasted wave heights primarily depend on the previous wave heights, while in larger lead times there is a greater dependence on previous wind speeds.

B. Kamranzad; A. Etemad-Shahidi; M.H. Kazeminezhad

2011-01-01T23:59:59.000Z

376

Cyberkelp: an integrative approach to the modelling of flexible organisms  

Science Journals Connector (OSTI)

...rope-like stipe that ends in a gas-filled, buoyant float, the...1536 M. W. Denny and B. B. Hale Cyberkelp: an integrative approach...approach M. W. Denny and B. B. Hale 1537 origin, d = x2 y2, is...1538 M. W. Denny and B. B. Hale Cyberkelp: an integrative approach...

2003-01-01T23:59:59.000Z

377

Empirical correction of a toy climate model  

Science Journals Connector (OSTI)

Improving the accuracy of forecast models for physical systems such as the atmosphere is a crucial ongoing effort. The primary focus of recent research on these highly nonlinear systems has been errors in state estimation, but as that error has been successfully diminished, the role of model error in forecast uncertainty has duly increased. The present study is an investigation of an empirical model correction procedure involving the comparison of short forecasts with a reference “truth” system during a training period, in order to calculate systematic (1) state-independent model bias and (2) state-dependent error patterns. An estimate of the likelihood of the latter error component is computed from the current state at every time step of model integration. The effectiveness of this technique is explored in a realistic scenario, in which the model is structurally different (in dynamics, dimension, and parametrization) from the target system. Results suggest that the correction procedure is more effective for reducing error and prolonging forecast usefulness than parameter tuning. However, the cost of this increase in average forecast accuracy is the creation of substantial qualitative differences between the dynamics of the corrected model and the true system. A method to mitigate dynamical ramifications and further increase forecast accuracy is presented.

Nicholas A. Allgaier; Kameron D. Harris; Christopher M. Danforth

2012-02-02T23:59:59.000Z

378

A comparison of Bayesian versus deterministic formulation for dynamic data integration into reservoir models  

E-Print Network [OSTI]

Into Reservoir Models. (Decmnber 200 I) Danny LL Rojas Paico, B. S. , Universidad Nacional de Ingenieria, Peru Chair of Advisory Committee: Dr. Akhil Datta-Gupta The integration of dynamic data into reservoir models is known as automatic history matching...

Rojas Paico, Danny H.

2001-01-01T23:59:59.000Z

379

Integrating Photovoltaic Inverter Reliability into Energy Yield Estimation with Markov Models  

E-Print Network [OSTI]

Integrating Photovoltaic Inverter Reliability into Energy Yield Estimation with Markov Models of the inverters. Keywords-Photovoltaic energy conversion, Markov reliability models, utility-interactive inverters, energy yield estimation. I. INTRODUCTION Photovoltaic systems have gained prominence as economically

Liberzon, Daniel

380

Reliability-yield allocation for semiconductor integrated circuits: modeling and optimization  

E-Print Network [OSTI]

This research develops yield and reliability models for fault-tolerant semiconductor integrated circuits and develops optimization algorithms that can be directly applied to these models. Since defects cause failures in microelectronics systems...

Ha, Chunghun

2005-11-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Methodologies for statistical behavioral modeling and simulation of complex analog integrated circuits  

E-Print Network [OSTI]

The objective of this thesis is to develop efficient methodologies for statistical behavioral modeling of analog integrated circuits and apply them to practical problems. Through appropriate statistical modeling, the Design for Quality (DFQ...

Swidzinski, Jan

2012-06-07T23:59:59.000Z

382

Integrated modelling of water availability and water use in the semi-arid Northeast of Brazil  

E-Print Network [OSTI]

Integrated modelling of water availability and water use in the semi-arid Northeast of Brazil A: Bronstert 1 Integrated modelling of water availability and water use in the semi-arid Northeast of Brazil A con- straint for development in the semi-arid Northeast of Brazil. Quanti cation of natural water

Bronstert, Axel

383

Finite element modeling of nonlinear vibration behavior of piezo-integrated structures  

Science Journals Connector (OSTI)

This paper aims at finite element modeling of nonlinear vibration behavior of piezo-integrated structures subjected to weak electric field. This nonlinear vibration behavior was observed in the form of dependence of resonance frequency on the vibration ... Keywords: Finite element modeling, Modal reduction, Newmark method, Nonlinear vibration, Piezo-integrated structures

Sandeep Kumar Parashar; Utz Von Wagner; Peter Hagedorn

2013-04-01T23:59:59.000Z

384

Metaprogrammable Toolkit for Model-Integrated Computing Akos Ledeczi, Miklos Maroti, Gabor Karsai and Greg Nordstrom  

E-Print Network [OSTI]

building, constraint management, and automatic program synthesis components, are well suited for the design. Model-Integrated Computing (MIC) is well suited for the rapid design and implementation of such systemsMetaprogrammable Toolkit for Model-Integrated Computing Akos Ledeczi, Miklos Maroti, Gabor Karsai

Maróti, Miklós

385

Design and Integration of Partial Brain Models Using Hierarchical Cooperative CoEvolution  

E-Print Network [OSTI]

Design and Integration of Partial Brain Models Using Hierarchical Cooperative CoEvolution Michail and integrating brain-inspired artificial cognitive sys- tems. Specifically, we introduce a new computational framework for modelling partial brain areas following a coevolutionary agent-based approach. Properly for

Trahanias, Panos

386

Integrating Models and Simulations of Continuous Dynamics into SysML  

E-Print Network [OSTI]

and the corresponding Modelica models; and the integration of simulation experiments with other SysML constructsIntegrating Models and Simulations of Continuous Dynamics into SysML Thomas Johnson1 Christiaan J.J. Paredis1 Roger Burkhart2 1 Systems Realization Laboratory The G. W. Woodruff School of Mechanical

387

NOAA Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps  

E-Print Network [OSTI]

Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12;Bay Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12 N Collier N Charlotte S Charlotte NOAA Harmful Algal Bloom Operational Forecast System Southwest

388

Integrated Assessment Modeling of Carbon Sequestration and Land Use Emissions Using Detailed Model Results and Observations  

SciTech Connect (OSTI)

This report outlines the progress on the development and application of Integrated Assessment Modeling of Carbon Sequestrations and Land Use Emissions supported by the DOE Office of Biological and Environmental Research (OBER), U.S. Department of Energy, Grant No. DOE-DE-FG02-01ER63069. The overall objective of this collaborative project between the University of Illinois at Urbana-Champaign (UIUC), Oak Ridge National Laboratory (ORNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL) was to unite the latest advances in carbon cycle research with scientifically based models and policy-related integrated assessment tools that incorporate computationally efficient representations of the latest knowledge concerning science and emission trajectories, and their policy implications. As part of this research we accomplished the following tasks that we originally proposed: (1) In coordination with LLNL and ORNL, we enhanced the Integrated Science Assessment Model's (ISAM) parametric representation of the ocean and terrestrial carbon cycles that better represent spatial and seasonal variations, which are important to study the mechanisms that influence carbon sequestration in the ocean and terrestrial ecosystems; (2) Using the MiniCAM modeling capability, we revised the SRES (IPCC Special Report on Emission Scenarios; IPCC, 2000) land use emission scenarios; and (3) On the application front, the enhanced version of ISAM modeling capability is applied to understand how short- and long-term natural carbon fluxes, carbon sequestration, and human emissions contribute to the net global emissions (concentrations) trajectories required to reach various concentration (emission) targets. Under this grant, 21 research publications were produced. In addition, this grant supported a number of graduate and undergraduate students whose fundamental research was to learn a disciplinary field in climate change (e.g., ecological dynamics and ocean circulations) and then complete research on how this field could be linked to the other factors we need to consider in its dynamics (e.g., land use, ocean and terrestrial carbon sequestration and climate change).

Dr. Atul Jain

2005-04-17T23:59:59.000Z

389

Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis  

E-Print Network [OSTI]

analyses of regional mod- eling with Polar WRF have been performed with results compared to selected localEvaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air.1.1 of the Weather Research and Forecasting model (WRF), a highresolution regional scale model, is used to simulate

Howat, Ian M.

390

Forecast Energy | Open Energy Information  

Open Energy Info (EERE)

Forecast Energy Forecast Energy Jump to: navigation, search Name Forecast Energy Address 2320 Marinship Way, Suite 300 Place Sausalito, California Zip 94965 Sector Services Product Intelligent Monitoring and Forecasting Services Year founded 2010 Number of employees 11-50 Company Type For profit Website http://www.forecastenergy.net Coordinates 37.865647°, -122.496315° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.865647,"lon":-122.496315,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

391

Price forecasting for notebook computers  

E-Print Network [OSTI]

This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a series of time periods, and the rates of change in the influence...

Rutherford, Derek Paul

2012-06-07T23:59:59.000Z

392

Forecasting phenology under global warming  

Science Journals Connector (OSTI)

...Forrest Forecasting phenology under global warming Ines Ibanez 1 * Richard B. Primack...and site-specific responses to global warming. We found that for most species...climate change|East Asia, global warming|growing season, hierarchical...

2010-01-01T23:59:59.000Z

393

Demand Forecasting of New Products  

E-Print Network [OSTI]

Keeping Unit or SKU) employing attribute analysis techniques. The objective of this thesis is to improve Abstract This thesis is a study into the demand forecasting of new products (also referred to as Stock

Sun, Yu

394

Valuing Climate Impacts in Integrated Assessment Models: The MIT IGSM  

E-Print Network [OSTI]

We discuss a strategy for investigating the impacts of climate change on Earth’s physical, biological and human resources and links to their socio-economic consequences. The features of the integrated global system framework ...

Reilly, John

2012-05-22T23:59:59.000Z

395

Advanced modeling of planarization processes for integrated circuit fabrication  

E-Print Network [OSTI]

Planarization processes are a key enabling technology for continued performance and density improvements in integrated circuits (ICs). Dielectric material planarization is widely used in front-end-of-line (FEOL) processing ...

Fan, Wei, Ph. D. Massachusetts Institute of Technology

2012-01-01T23:59:59.000Z

396

Solar forecasting review  

E-Print Network [OSTI]

of all Numerical Weather Prediction (NWP models). First aof all Numerical Weather Prediction (NWP models). First apersistence models, numerical weather predictions as well as

Inman, Richard Headen

2012-01-01T23:59:59.000Z

397

Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting  

E-Print Network [OSTI]

This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting ...

Goto, Susumu

2007-01-01T23:59:59.000Z

398

A real time model to forecast 24 hours ahead, ozone peaks and exceedance levels. Model based on artificial neural networks, neural classifier and weather predictions.  

E-Print Network [OSTI]

on artificial neural networks, neural classifier and weather predictions. Application in an urban atmosphere - will be solved. Keywords: Artificial neural network; Multilayer Perceptron; ozone modelling; statistical stepwise and Software 22, 9 (2007) 1261-1269" DOI : 10.1016/j.envsoft.2006.08.002 #12;Abstract A neural network combined

Paris-Sud XI, Université de

399

USE OF AN EQUILIBRIUM MODEL TO FORECAST DISSOLUTION EFFECTIVENESS, SAFETY IMPACTS, AND DOWNSTREAM PROCESSABILITY FROM OXALIC ACID AIDED SLUDGE REMOVAL IN SAVANNAH RIVER SITE HIGH LEVEL WASTE TANKS 1-15  

SciTech Connect (OSTI)

This thesis details a graduate research effort written to fulfill the Magister of Technologiae in Chemical Engineering requirements at the University of South Africa. The research evaluates the ability of equilibrium based software to forecast dissolution, evaluate safety impacts, and determine downstream processability changes associated with using oxalic acid solutions to dissolve sludge heels in Savannah River Site High Level Waste (HLW) Tanks 1-15. First, a dissolution model is constructed and validated. Coupled with a model, a material balance determines the fate of hypothetical worst-case sludge in the treatment and neutralization tanks during each chemical adjustment. Although sludge is dissolved, after neutralization more is created within HLW. An energy balance determines overpressurization and overheating to be unlikely. Corrosion induced hydrogen may overwhelm the purge ventilation. Limiting the heel volume treated/acid added and processing the solids through vitrification is preferred and should not significantly increase the number of glass canisters.

KETUSKY, EDWARD

2005-10-31T23:59:59.000Z

400

Random switching exponential smoothing and inventory forecasting  

Science Journals Connector (OSTI)

Abstract Exponential smoothing models represent an important prediction tool both in business and in macroeconomics. This paper provides the analytical forecasting properties of the random coefficient exponential smoothing model in the “multiple source of error” framework. The random coefficient state-space representation allows for switching between simple exponential smoothing and local linear trend. Therefore it enables controlling, in a flexible manner, the random changing dynamic behavior of the time series. The paper establishes the algebraic mapping between the state-space parameters and the implied reduced form ARIMA parameters. In addition, it shows that the parametric mapping allows overcoming the difficulties that are likely to emerge in estimating directly the random coefficient state-space model. Finally, it presents an empirical application comparing the forecast accuracy of the suggested model vis-à-vis other benchmark models, both in the ARIMA and in the exponential smoothing class. Using time series relative to wholesalers inventories in the USA, the out-of-sample results show that the reduced form of the random coefficient exponential smoothing model tends to be superior to its competitors.

Giacomo Sbrana; Andrea Silvestrini

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Wind Forecast Improvement Project Southern Study Area Final Report...  

Office of Environmental Management (EM)

Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern...

402

Applying Bayesian Forecasting to Predict New Customers' Heating Oil Demand.  

E-Print Network [OSTI]

??This thesis presents a new forecasting technique that estimates energy demand by applying a Bayesian approach to forecasting. We introduce our Bayesian Heating Oil Forecaster… (more)

Sakauchi, Tsuginosuke

2011-01-01T23:59:59.000Z

403

Probabilistic electricity price forecasting with variational heteroscedastic Gaussian process and active learning  

Science Journals Connector (OSTI)

Abstract Electricity price forecasting is essential for the market participants in their decision making. Nevertheless, the accuracy of such forecasting cannot be guaranteed due to the high variability of the price data. For this reason, in many cases, rather than merely point forecasting results, market participants are more interested in the probabilistic price forecasting results, i.e., the prediction intervals of the electricity price. Focusing on this issue, this paper proposes a new model for the probabilistic electricity price forecasting. This model is based on the active learning technique and the variational heteroscedastic Gaussian process (VHGP). It provides the heteroscedastic Gaussian prediction intervals, which effectively quantify the heteroscedastic uncertainties associated with the price data. Because the high computational effort of VHGP hinders its application to the large-scale electricity price forecasting tasks, we design an active learning algorithm to select a most informative training subset from the whole available training set. By constructing the forecasting model on this smaller subset, the computational efforts can be significantly reduced. In this way, the practical applicability of the proposed model is enhanced. The forecasting performance and the computational time of the proposed model are evaluated using the real-world electricity price data, which is obtained from the ANEM, PJM, and New England ISO.

Peng Kou; Deliang Liang; Lin Gao; Jianyong Lou

2015-01-01T23:59:59.000Z

404

Comodeling: From Requirements to an Integrated Software/Hardware Model  

Science Journals Connector (OSTI)

Comodeling lets developers systematically investigate and compare different software and hardware partitions to meet a system's constraints earlier in the design process, when integration problems are easier and cheaper to resolve. Keywords: Systems engineering, Hardware/software codesign, Comodeling, Behavior engineering, Modelica, Requirements engineering, Hybrid simulation, Behavior trees

Toby Myers; Geoff Dromey; Peter Fritzson

2011-04-01T23:59:59.000Z

405

European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind Generation by a Dynamic  

E-Print Network [OSTI]

European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind forecasting. I. INTRODUCTION HE actual large-scale integration of wind energy in several European countries enhance the position of wind energy compared to other dispatchable forms of generation. Predicting

Paris-Sud XI, Université de

406

Forecasting Building Occupancy Using Sensor Network James Howard  

E-Print Network [OSTI]

) into the future. Our approach is to train a set of standard forecasting models to our time series data. Each model conditioning (HVAC) systems. In particular, if occupancy can be accurately pre- dicted, HVAC systems can potentially be controlled to op- erate more efficiently. For example, an HVAC system can pre-heat or pre

Hoff, William A.

407

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations – the Northern Study Area.  

SciTech Connect (OSTI)

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times. A comprehensive analysis of wind energy forecast errors for the various model-based power forecasts was presented for a suite of wind energy ramp definitions. The results compiled over the year-long study period showed that the power forecasts based on the research models (ESRL_RAP, HRRR) more accurately predict wind energy ramp events than the current operational forecast models, both at the system aggregate level and at the local wind plant level. At the system level, the ESRL_RAP-based forecasts most accurately predict both the total number of ramp events and the occurrence of the events themselves, but the HRRR-based forecasts more accurately predict the ramp rate. At the individual site level, the HRRR-based forecasts most accurately predicted the actual ramp occurrence, the total number of ramps and the ramp rates (40-60% improvement in ramp rates over the coarser resolution forecast

Finley, Cathy [WindLogics

2014-04-30T23:59:59.000Z

408

Solar Energy Market Forecast | Open Energy Information  

Open Energy Info (EERE)

Solar Energy Market Forecast Solar Energy Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast Agency/Company /Organization: United States Department of Energy Sector: Energy Focus Area: Solar Topics: Market analysis, Technology characterizations Resource Type: Publications Website: giffords.house.gov/DOE%20Perspective%20on%20Solar%20Market%20Evolution References: Solar Energy Market Forecast[1] Summary " Energy markets / forecasts DOE Solar America Initiative overview Capital market investments in solar Solar photovoltaic (PV) sector overview PV prices and costs PV market evolution Market evolution considerations Balance of system costs Silicon 'normalization' Solar system value drivers Solar market forecast Additional resources"

409

Submitted to the Annals of Applied Statistics INTEGRATIVE MODEL-BASED CLUSTERING OF MICROARRAY  

E-Print Network [OSTI]

, Expression, AML. 1 #12;2 KORMAKSSON ET AL. can guide the design of more specifically targeted therapies. DueSubmitted to the Annals of Applied Statistics INTEGRATIVE MODEL-BASED CLUSTERING OF MICROARRAY to multiple data types of a similar nature, which leads to an integrated analysis over multiple data platforms

Booth, James

410

Patterns for Business Object Model Integration in Process-Driven and Service-Oriented Architectures  

E-Print Network [OSTI]

Patterns for Business Object Model Integration in Process-Driven and Service-Oriented Architectures-Mail: zdun@acm.org Service-oriented architectures often have the goal to integrate various systems of one of various external systems into a consistent process-driven and service- oriented architecture. Introduction

Zdun, Uwe

411

An Exact Modeling of Signal Statistics in Energy-integrating X-ray Computed Tomography  

E-Print Network [OSTI]

assumption was made that the number of x-ray quanta within an energy interval in the spectrum followsAn Exact Modeling of Signal Statistics in Energy-integrating X-ray Computed Tomography Yi Fan1 School of Medicine, Atlanta, GA 30322 ABSTRACT Energy-integrating detection of x-ray sources is widely

412

Modeling and Optimization of Membrane Reactors for Carbon Capture in Integrated Gasification Combined Cycle Units  

Science Journals Connector (OSTI)

Modeling and Optimization of Membrane Reactors for Carbon Capture in Integrated Gasification Combined Cycle Units ... This paper investigates the alternative of precombustion capture of carbon dioxide from integrated gasification combined cycle (IGCC) plants using membrane reactors equipped with H2-selective zeolite membranes for the water gas shift reaction. ...

Fernando V. Lima; Prodromos Daoutidis; Michael Tsapatsis; John J. Marano

2012-03-08T23:59:59.000Z

413

Multiscale Strategic Planning Model for the Design of Integrated Ethanol and Gasoline Supply Chain  

E-Print Network [OSTI]

1 Multiscale Strategic Planning Model for the Design of Integrated Ethanol and Gasoline Supply address the design and planning of an integrated ethanol and gasoline supply chain. We assume, distribution centers where blending takes place, and the retail gas stations where different blends of gasoline

Grossmann, Ignacio E.

414

EWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology The Anemos Wind Power Forecasting Platform Technology -  

E-Print Network [OSTI]

EWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology 1 The Anemos Wind Power a professional, flexible platform for operating wind power prediction models, laying the main focus on state models from all over Europe are able to work on this platform. Keywords: wind energy, wind power

Boyer, Edmond

415

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching  

E-Print Network [OSTI]

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at a wind energy site and fits a conditional predictive model for each regime. Geographically dispersed was applied to 2-hour-ahead forecasts of hourly average wind speed near the Stateline wind energy center

Genton, Marc G.

416

Dynamics and Structure of Forecast Error Covariance in the Core of a Developing Hurricane  

E-Print Network [OSTI]

of cloud-resolving forecasts from the Weather Research and Forecasting model (WRF) was used to study error gradients of wind, temperature, and pressure to be concentrated farther from the mean vortex center share a similar axisymmetric transition about the origin, while maintaining a large degree of local

417

Univariate forecasting of day-ahead hourly electricity demand in the northern grid of India  

Science Journals Connector (OSTI)

Short-term electricity demand forecasts (minutes to several hours ahead) have become increasingly important since the rise of the competitive energy markets. The issue is particularly important for India as it has recently set up a power exchange (PX), which has been operating on day-ahead hourly basis. In this study, an attempt has been made to forecast day-ahead hourly demand of electricity in the northern grid of India using univariate time-series forecasting techniques namely multiplicative seasonal ARIMA and Holt-Winters multiplicative exponential smoothing (ES). In-sample forecasts reveal that ARIMA models, except in one case, outperform ES models in terms of lower RMSE, MAE and MAPE criteria. We may conclude that linear time-series models works well to explain day-ahead hourly demand forecasts in the northern grid of India. The findings of the study will immensely help the players in the upcoming power market in India.

Sajal Ghosh

2009-01-01T23:59:59.000Z

418

Application of GIS on forecasting water disaster in coal mines  

SciTech Connect (OSTI)

In many coal mines of China, water disasters occur very frequently. It is the most important problem that water gets inrush into drifts and coal faces, locally known as water gush, during extraction and excavation. Its occurrence is controlled by many factors such as geological, hydrogeological and mining technical conditions, and very difficult to be predicted and prevented by traditional methods. By making use of overlay analysis of Geographic Information System, a multi-factor model can be built to forecast the potential of water gush. This paper introduced the method of establishment of the water disaster forecasting system and forecasting model and two practical successful cases of application in Jiaozuo and Yinzhuang coal mines. The GIS proved helpful for ensuring the safety of coal mines.

Sun Yajun; Jiang Dong; Ji Jingxian [China Univ. of Mining and Technology, Jiangshy (China)] [and others

1996-08-01T23:59:59.000Z

419

Wave Tank Testing and Model Validation Â… An Integrated Approach  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Wave Tank Testing and Model Validation - Lessons Learned Wave Tank Testing and Model Validation - Lessons Learned Mirko Previsic 7-7-12 2 Representing the Full-Scale System P, V qv q T u q Generator Guide vanes Turbine Blades Configuration 3 Appropriate Modeling of Physics Run-time is important to make a model useful as an engineering and/or optimization tool. * Have to be selective about how the physics is represented in the model * Different physical phenomena are important to different WEC devices Subscale modeling allows to help us understand and validate the models physics. * Ideally we can isolate physical phenomena to properly debug theoretical model * Focus is on validating fluid-structure interaction * Scaling of mechanical systems needs to represent the physics of the full- scale system (i.e. mooring, power-take-off, control system).

420

Utility system integration and optimization models for nuclear power management  

E-Print Network [OSTI]

A nuclear power management model suitable for nuclear utility systems optimization has been developed for use in multi-reactor fuel management planning over periods of up to ten years. The overall utility planning model ...

Deaton, Paul Ferris

1973-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Modeling a solar energy collector with an integrated phase-change material  

E-Print Network [OSTI]

In this thesis, a finite-element computer model was created to simulate a solar air heater with an integrated-phase change material. The commercially available finite element package ADINA-Fluid was used to generate the ...

Guerra, Alexander Adrian

2009-01-01T23:59:59.000Z

422

Modeling a solar energy collector with an integrated phase-change material .  

E-Print Network [OSTI]

??In this thesis, a finite-element computer model was created to simulate a solar air heater with an integrated-phase change material. The commercially available finite element… (more)

Guerra, Alexander Adrian

2009-01-01T23:59:59.000Z

423

Integrated modelling and assessment of regional groundwater resources in Germany and Benin, West Africa  

E-Print Network [OSTI]

1 Integrated modelling and assessment of regional groundwater resources in Germany and Benin, West.J.S. SONNEVELD [1] Institute of Hydraulic Engineering, Universitaet Stuttgart, Germany (Roland Conservation University of Bonn, Germany [3] Institute of Landscape Planning and Ecology, University

Cirpka, Olaf Arie

424

Analysis of Integration Models for Service Composition Dept. of Electrical Engineering  

E-Print Network [OSTI]

Analysis of Integration Models for Service Composition David Liu Dept. of Electrical Engineering. Other services include simulation programs [16], engineering, logistics, and business services & Environmental Engineering Stanford University Stanford, CA 94305, USA law@cive.stanford.edu Gio Wiederhold

Stanford University

425

Modeling Methodology for Component Reuse and System Integration for Hurricane Loss Projection Application  

E-Print Network [OSTI]

Modeling Methodology for Component Reuse and System Integration for Hurricane Loss Projection Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University, Miami, FL 33199, USA 2 Department of Finance Florida International University, Miami

Chen, Shu-Ching

426

Volatility forecasting with smooth transition exponential smoothing  

Science Journals Connector (OSTI)

Adaptive exponential smoothing methods allow smoothing parameters to change over time, in order to adapt to changes in the characteristics of the time series. This paper presents a new adaptive method for predicting the volatility in financial returns. It enables the smoothing parameter to vary as a logistic function of user-specified variables. The approach is analogous to that used to model time-varying parameters in smooth transition generalised autoregressive conditional heteroskedastic (GARCH) models. These non-linear models allow the dynamics of the conditional variance model to be influenced by the sign and size of past shocks. These factors can also be used as transition variables in the new smooth transition exponential smoothing (STES) approach. Parameters are estimated for the method by minimising the sum of squared deviations between realised and forecast volatility. Using stock index data, the new method gave encouraging results when compared to fixed parameter exponential smoothing and a variety of GARCH models.

James W. Taylor

2004-01-01T23:59:59.000Z

427

Statistics Useful for Deterministic Models: Evaluation, Calibration, Extension, Integration,  

E-Print Network [OSTI]

processing) Data assimilation · Postprocessing of model output ­ Model evaluation/assessment ­ Model in the manipulated data 6 #12;Comparison of GOES satellite data with EPA PM observations · half-hourly GOES aerosol 1, 2006 www.biostat.harvard.edu/~paciorek LYX - FoilTEX - pdfLATEX #12;Uses of Data and Statistics

Paciorek, Chris

428

Forecasting for inventory control with exponential smoothing  

Science Journals Connector (OSTI)

Exponential smoothing, often used in sales forecasting for inventory control, has always been rationalized in terms of statistical models that possess errors with constant variances. It is shown in this paper that exponential smoothing remains appropriate under more general conditions, where the variance is allowed to grow or contract with corresponding movements in the underlying level. The implications for estimation and prediction are explored. In particular, the problem of finding the predictive distribution of aggregate lead-time demand, for use in inventory control calculations, is considered using a bootstrap approach. A method for establishing order-up-to levels directly from the simulated predictive distribution is also explored.

Ralph D. Snyder; Anne B. Koehler; J.Keith Ord

2002-01-01T23:59:59.000Z

429

Integrating Parallel DEVS and equation-based object-oriented modeling  

Science Journals Connector (OSTI)

The benefits of integrating the Parallel DEVS (P-DEVS) formalism with the Equation-Based Object-Oriented modeling languages (EOOL), which constitute the state-of-the-art for continuous-time system modeling, are discussed. The characteristics of the Equation-Based ... Keywords: Modelica, equation-based language, hybrid systems, object-oriented modeling, parallel DEVS

Victorino Sanz; Alfonso Urquia; Sebastian Dormido

2010-04-01T23:59:59.000Z

430

Summary Verification Measures and Their Interpretation for Ensemble Forecasts  

Science Journals Connector (OSTI)

Ensemble prediction systems produce forecasts that represent the probability distribution of a continuous forecast variable. Most often, the verification problem is simplified by transforming the ensemble forecast into probability forecasts for ...

A. Allen Bradley; Stuart S. Schwartz

2011-09-01T23:59:59.000Z

431

Integrating Empirical-Modeling Approaches to Improve Understanding of Terrestrial Ecology Processes  

SciTech Connect (OSTI)

Recent decades have seen tremendous increases in the quantity of empirical ecological data collected by individual investigators, as well as through research networks such as FLUXNET (Baldocchi et al., 2001). At the same time, advances in computer technology have facilitated the development and implementation of large and complex land surface and ecological process models. Separately, each of these information streams provides useful, but imperfect information about ecosystems. To develop the best scientific understanding of ecological processes, and most accurately predict how ecosystems may cope with global change, integration of empirical and modeling approaches is necessary. However, true integration - in which models inform empirical research, which in turn informs models (Fig. 1) - is not yet common in ecological research (Luo et al., 2011). The goal of this workshop, sponsored by the Department of Energy, Office of Science, Biological and Environmental Research (BER) program, was to bring together members of the empirical and modeling communities to exchange ideas and discuss scientific practices for increasing empirical - model integration, and to explore infrastructure and/or virtual network needs for institutionalizing empirical - model integration (Yiqi Luo, University of Oklahoma, Norman, OK, USA). The workshop included presentations and small group discussions that covered topics ranging from model-assisted experimental design to data driven modeling (e.g. benchmarking and data assimilation) to infrastructure needs for empirical - model integration. Ultimately, three central questions emerged. How can models be used to inform experiments and observations? How can experimental and observational results be used to inform models? What are effective strategies to promote empirical - model integration?

McCarthy, Heather [University of Oklahoma; Luo, Yiqi [University of Oklahoma; Wullschleger, Stan D [ORNL

2012-01-01T23:59:59.000Z

432

Testing Competing Precipitation Forecasts Accurately and Efficiently: The Spatial Prediction Comparison Test  

Science Journals Connector (OSTI)

Which model is best? Many challenges exist when testing competing forecast models, especially for those with high spatial resolution. Spatial correlation, double penalties, and small-scale errors are just a few such challenges. Many new methods ...

Eric Gilleland

2013-01-01T23:59:59.000Z

433

Using Google Flu Trends data in forecasting influenza-like–illness related ED visits in Omaha, Nebraska  

Science Journals Connector (OSTI)

AbstractIntroduction Emergency department (ED) visits increase during the influenza seasons. It is essential to identify statistically significant correlates in order to develop an accurate forecasting model for ED visits. Forecasting influenza-like–illness (ILI)-related ED visits can significantly help in developing robust resource management strategies at the EDs. Methods We first performed correlation analyses to understand temporal correlations between several predictors of ILI-related ED visits. We used the data available for Douglas County, the biggest county in Nebraska, for Omaha, the biggest city in the state, and for a major hospital in Omaha. The data set included total and positive influenza test results from the hospital (ie, Antigen rapid (Ag) and Respiratory Syncytial Virus Infection (RSV) tests); an Internet-based influenza surveillance system data, that is, Google Flu Trends, for both Nebraska and Omaha; total ED visits in Douglas County attributable to ILI; and ILI surveillance network data for Douglas County and Nebraska as the predictors and data for the hospital's ILI-related ED visits as the dependent variable. We used Seasonal Autoregressive Integrated Moving Average and Holt Winters methods with3 linear regression models to forecast ILI-related ED visits at the hospital and evaluated model performances by comparing the root means square errors (RMSEs). Results Because of strong positive correlations with ILI-related ED visits between 2008 and 2012, we validated the use of Google Flu Trends data as a predictor in an ED influenza surveillance tool. Of the 5 forecasting models we have tested, linear regression models performed significantly better when Google Flu Trends data were included as a predictor. Regression models including Google Flu Trends data as a predictor variable have lower RMSE, and the lowest is achieved when all other variables are also included in the model in our forecasting experiments for the first 5 weeks of 2013 (with RMSE = 57.61). Conclusions Google Flu Trends data statistically improve the performance of predicting ILI-related ED visits in Douglas County, and this result can be generalized to other communities. Timely and accurate estimates of ED volume during the influenza season, as well as during pandemic outbreaks, can help hospitals plan their ED resources accordingly and lower their costs by optimizing supplies and staffing and can improve service quality by decreasing ED wait times and overcrowding.

Ozgur M. Araz; Dan Bentley; Robert L. Muelleman

2014-01-01T23:59:59.000Z

434

Integrated Market Modeling of Hydrogen Transition Scenarios with HyTrans  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Integrated Market Modeling of Integrated Market Modeling of Hydrogen Transition Scenarios with HyTrans Paul N. Leiby, David L. Greene and David Bowman Oak Ridge National Laboratory A presentation to the Hydrogen Delivery Analysis Meeting FreedomCAR and Fuels Partnership Delivery, Storage and Hydrogen Pathways Tech Teams May 8-9, 2007 Columbia, MD 2 OAK RIDGE NATIONAL LABORATORY U. S. DEPARTMENT OF ENERGY Drawing from several other DOE models, HyTrans integrates supply and demand in a dynamic non-linear market model to 2050. * H2A - Hydrogen Production - Hydrogen Delivery * PSAT & ASCM - Fuel economy - 2010/2015 cost & performance goals * ORNL Vehicle Choice Model - Fuel availability - Make & model diversity - Price, fuel economy, etc. * Vehicle Manufacturing Cost Estimates (assisted by OEMs)

435

Communication of uncertainty in temperature forecasts  

Science Journals Connector (OSTI)

We used experimental economics to test whether undergraduate students presented with a temperature forecast with uncertainty information in a table and bar graph format were able to use the extra information to interpret a given forecast. ...

Pricilla Marimo; Todd R. Kaplan; Ken Mylne; Martin Sharpe

436

FORECASTING THE ROLE OF RENEWABLES IN HAWAII  

E-Print Network [OSTI]

FORECASTING THE ROLE OF RENEWABLES IN HAWAII Jayant SathayeFORECASTING THE ROLF OF RENEWABLES IN HAWAII J Sa and Henrythe Conservation Role of Renewables November 18, 1980 Page 2

Sathaye, Jayant

2013-01-01T23:59:59.000Z

437

Massachusetts state airport system plan forecasts.  

E-Print Network [OSTI]

This report is a first step toward updating the forecasts contained in the 1973 Massachusetts State System Plan. It begins with a presentation of the forecasting techniques currently available; it surveys and appraises the ...

Mathaisel, Dennis F. X.

438

Antarctic Satellite Meteorology: Applications for Weather Forecasting  

Science Journals Connector (OSTI)

For over 30 years, weather forecasting for the Antarctic continent and adjacent Southern Ocean has relied on weather satellites. Significant advancements in forecasting skill have come via the weather satellite. The advent of the high-resolution ...

Matthew A. Lazzara; Linda M. Keller; Charles R. Stearns; Jonathan E. Thom; George A. Weidner

2003-02-01T23:59:59.000Z

439

Forecasting Water Use in Texas Cities  

E-Print Network [OSTI]

In this research project, a methodology for automating the forecasting of municipal daily water use is developed and implemented in a microcomputer program called WATCAL. An automated forecast system is devised by modifying the previously...

Shaw, Douglas T.; Maidment, David R.

440

Analysis of kinetic models of the methanol-to-gasoline (MTG) process in an integral reactor  

Science Journals Connector (OSTI)

From experimental results obtained in a wide range of operating conditions (temperature and contact time) in an isothermal fixed bed integral reactor, the validity both of the kinetic models proposed in the literature as well as their modifications, for the methanol-to-gasoline (MTG) process at zero time on-stream, has been studied. The kinetic parameters for the various models have been calculated by solving the equation of mass conservation in the reactor for the lumps of the kinetic models. The usefulness of the model of Schipper and Krambeck for simulating the operation in the isothermal fixed bed integral reactor has been proven in the 573–648 K range.

Ana G. Gayubo; Pedro L. Benito; Andrés T. Aguayo; Itziar Aguirre; Javier Bilbao

1996-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Contacts Contacts The International Energy Outlook is prepared by the Energy Information Administration (EIA). General questions concerning the contents of the report should be referred to John J. Conti (john.conti@eia.doe.gov, 202-586-2222), Director, Office of Integrated Analysis and Forecasting. Specific questions about the report should be referred to Linda E. Doman (202/586-1041) or the following analysts: World Energy and Economic Outlook Linda Doman (linda.doman@eia.doe.gov, 202-586-1041) Macroeconomic Assumptions Nasir Khilji (nasir.khilji@eia.doe.gov, 202-586-1294) Energy Consumption by End-Use Sector Residential Energy Use John Cymbalsky (john.cymbalsky@eia.doe.gov, 202-586-4815) Commercial Energy Use Erin Boedecker (erin.boedecker@eia.doe.gov, 202-586-4791)

442

Technology data characterizing space conditioning in commercial buildings: Application to end-use forecasting with COMMEND 4.0  

SciTech Connect (OSTI)

In the US, energy consumption is increasing most rapidly in the commercial sector. Consequently, the commercial sector is becoming an increasingly important target for state and federal energy policies and also for utility-sponsored demand side management (DSM) programs. The rapid growth in commercial-sector energy consumption also makes it important for analysts working on energy policy and DSM issues to have access to energy end-use forecasting models that include more detailed representations of energy-using technologies in the commercial sector. These new forecasting models disaggregate energy consumption not only by fuel type, end use, and building type, but also by specific technology. The disaggregation of space conditioning end uses in terms of specific technologies is complicated by several factors. First, the number of configurations of heating, ventilating, and air conditioning (HVAC) systems and heating and cooling plants is very large. Second, the properties of the building envelope are an integral part of a building`s HVAC energy consumption characteristics. Third, the characteristics of commercial buildings vary greatly by building type. The Electric Power Research Institute`s (EPRI`s) Commercial End-Use Planning System (COMMEND 4.0) and the associated data development presented in this report attempt to address the above complications and create a consistent forecasting framework. This report describes the process by which the authors collected space-conditioning technology data and then mapped it into the COMMEND 4.0 input format. The data are also generally applicable to other end-use forecasting frameworks for the commercial sector.

Sezgen, O.; Franconi, E.M.; Koomey, J.G.; Greenberg, S.E.; Afzal, A.; Shown, L.

1995-12-01T23:59:59.000Z

443

THE INTEGRATION MODELING FRAMEWORK FOR ESTIMATING MOBILE SOURCE EMISSIONS  

E-Print Network [OSTI]

@vt.edu. #12;Rakha and Ahn 2 the environmental impacts of ITS alternatives. The model combines car dynamics. Consequently, the assessment of the energy and emission impacts of alternative investments can-following, vehicle dynamics, lane changing, energy, and emission models to estimate mobile source emissions directly

Rakha, Hesham A.

444

Interaction with a field: a simple integrable model with backreaction  

E-Print Network [OSTI]

involving electromagnetic fields -- this paper discusses a simple model of an oscillator coupled to a string considering the interaction of an atom (the oscillator) with light (the string). First (§ 3), when the string.40.Cd, 46.40.Ff, 42.50.Ct, 03.65.Yz. Abstract The classical model of an oscillator linearly coupled

Boyer, Edmond

445

Consensus Coal Production And Price Forecast For  

E-Print Network [OSTI]

Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 © Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast

Mohaghegh, Shahab

446

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation Analysis Papers > Annual Energy Outlook Forecast Evaluation Release Date: February 2005 Next Release Date: February 2006 Printer-friendly version Annual Energy Outlook Forecast Evaluation* Table 1.Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Printer Friendly Version Average Absolute Percent Error Variable AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 AEO82 to AEO2004 Consumption Total Energy Consumption 1.9 2.0 2.1 2.1 2.1 2.1 Total Petroleum Consumption 2.9 3.0 3.1 3.1 3.0 2.9 Total Natural Gas Consumption 7.3 7.1 7.1 6.7 6.4 6.5 Total Coal Consumption 3.1 3.3 3.5 3.6 3.7 3.8 Total Electricity Sales 1.9 2.0 2.3 2.3 2.3 2.4 Production Crude Oil Production 4.5 4.5 4.5 4.5 4.6 4.7

447

Load Forecasting of Supermarket Refrigeration  

E-Print Network [OSTI]

energy system. Observed refrigeration load and local ambient temperature from a Danish su- permarket renewable energy, is increasing, therefore a flexible energy system is needed. In the present ThesisLoad Forecasting of Supermarket Refrigeration Lisa Buth Rasmussen Kongens Lyngby 2013 M.Sc.-2013

448

An Integrated Approach to Modeling and Mitigating SOFC Failure  

SciTech Connect (OSTI)

The specific objectives of this project were: (1) To develop and demonstrate the feasibility of an integrated predictive computer-based tool for fuel cell design and reliability/durability analysis, (2) To generate new scientific and engineering knowledge to better enable SECA Industry Teams to develop reliable, low-cost solid-oxide fuel cell power generation systems, (3) To create technology breakthroughs to address technical risks and barriers that currently limit achievement of the SECA performance and cost goals for solidoxide fuel cell systems, and (4) To transfer new science and technology developed in the project to the SECA Industry Teams. Through this three-year project, the Georgia Tech's team has demonstrated the feasibility of the solution proposed and the merits of the scientific path of inquiry, and has developed the technology to a sufficient level such that it can be utilized by the SECA Industry Teams. This report summarizes the project's results and achievements.

Jianmin Qu; Andrei Fedorov; Comas Haynes

2006-05-15T23:59:59.000Z

449

An integrated cost model for production scheduling and perfect maintenance  

Science Journals Connector (OSTI)

Production scheduling deals with scheduling production jobs on a machine (single or multiple) in order to optimise a specific objective such as total weighted completion times or total weighted tardiness. The assumption that machines are always available for processing jobs is generally used in the production scheduling literature. In reality, machines often are unavailable due to preventive maintenance activities or machine failure. Production scheduling and preventive maintenance planning are interrelated, but are most often treated separately. This interdependency seems to be overlooked in the literature. This work integrates, simultaneously, the decisions of preventive maintenance and job order sequencing for a single machine. The objective is to find the job order sequence and maintenance decisions that would minimise the expected cost.

Laith A. Hadidi; Umar M. Al-Turki; M. Abdur Rahim

2011-01-01T23:59:59.000Z

450

Integrated generic 3D visualization of Modelica models.  

E-Print Network [OSTI]

?? OpenModelica is a complete environment for developing and simulatingModelica models based on free software. It is promoted and developed bythe OpenModelica Consortium. This thesis… (more)

Magnusson, Henrik

2008-01-01T23:59:59.000Z

451

Integrating the common information model with MDS4  

Science Journals Connector (OSTI)

The management and monitoring of static and dynamic resources is a key issue in grid environments. Information models are an abstract representation of software and hardware aspects of these resources, a common and structured representation that allows ...

I. Diaz; G. Fernandez; M. J. Martinm; P. Gonzalez; J. Tourino

2008-09-01T23:59:59.000Z

452

URBAN MODELING FROM LIDAR DATA IN AN INTEGRATED GIS ENVIRONMENT  

E-Print Network [OSTI]

are analyzed and possible solutions are proposed by fusing lidar data with other image data. Study shows: it allows rapid generation large-scale DTM (digital terrain model); is daylight independent; is relatively

Shan, Jie

453

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks  

E-Print Network [OSTI]

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu an advantage for output power prediction. Solar Energy Prediction System Our prediction model is based variability of more then 100 kW per minute. For practical usage of solar energy, predicting times of high

Cerpa, Alberto E.

454

Development and Deployment of an Advanced Wind Forecasting Technique  

E-Print Network [OSTI]

findings. Part 2 addresses how operators of wind power plants and power systems can incorporate advanced the output of advanced wind energy forecasts into decision support models for wind power plant and power in Porto) Power Systems Unit Porto, Portugal Industry Partners Horizon Wind Energy, LLC Midwest Independent

Kemner, Ken

455

What constrains spread growth in forecasts ini2alized from  

E-Print Network [OSTI]

1 What constrains spread growth in forecasts ini2alized from ensemble Kalman filters? Tom from manner in which ini2al condi2ons are generated, some due to the model (e.g., stochas2c physics as error; part of spread growth from manner in which ini2al condi2ons are generated, some due

Hamill, Tom

456

Introduction An important goal in operational weather forecasting  

E-Print Network [OSTI]

sensitive areas. To answer these questions simulation experiments with state-of-the-art numerical weather prediction (NWP) models have proved great value to test future meteorological observing systems a priori102 Introduction An important goal in operational weather forecasting is to reduce the number

Haak, Hein

457

Forecasting-based SKU classification  

Science Journals Connector (OSTI)

Different spare parts are associated with different underlying demand patterns, which in turn require different forecasting methods. Consequently, there is a need to categorise stock keeping units (SKUs) and apply the most appropriate methods in each category. For intermittent demands, Croston's method (CRO) is currently regarded as the standard method used in industry to forecast the relevant inventory requirements; this is despite the bias associated with Croston's estimates. A bias adjusted modification to CRO (Syntetos–Boylan Approximation, SBA) has been shown in a number of empirical studies to perform very well and be associated with a very ‘robust’ behaviour. In a 2005 article, entitled ‘On the categorisation of demand patterns’ published by the Journal of the Operational Research Society, Syntetos et al. (2005) suggested a categorisation scheme, which establishes regions of superior forecasting performance between CRO and SBA. The results led to the development of an approximate rule that is expressed in terms of fixed cut-off values for the following two classification criteria: the squared coefficient of variation of the demand sizes and the average inter-demand interval. Kostenko and Hyndman (2006) revisited this issue and suggested an alternative scheme to distinguish between CRO and SBA in order to improve overall forecasting accuracy. Claims were made in terms of the superiority of the proposed approach to the original solution but this issue has never been assessed empirically. This constitutes the main objective of our work. In this paper the above discussed classification solutions are compared by means of experimentation on more than 10,000 \\{SKUs\\} from three different industries. The results enable insights to be gained into the comparative benefits of these approaches. The trade-offs between forecast accuracy and other implementation related considerations are also addressed.

G. Heinecke; A.A. Syntetos; W. Wang

2013-01-01T23:59:59.000Z

458

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations – the Southern Study Area  

SciTech Connect (OSTI)

This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP)--Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute – 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 – 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 – 3 hours.

Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

2014-04-30T23:59:59.000Z

459

An Integrated Model of Coal/Coke Combustion in a Blast Furnace  

Science Journals Connector (OSTI)

A three?dimensional integrated mathematical model of the combustion of pulverized coal and coke is developed. The model is applied to the region of lance?blowpipe?tuyere?raceway?coke bed to simulate the operation of pulverized coal injection in an ironmaking blast furnace. The model integrates two parts: pulverized coal combustion model in the blowpipe?tuyere?raceway?coke bed and the coke combustion model in the coke bed. The model is validated against the measurements in terms of coal burnout and gas composition respectively. The comprehensive in?furnace phenomena are simulated in the raceway and coke bed in terms of flow temperature gas composition and coal burning characteristics. In addition underlying mechanisms for the in?furnace phenomena are analyzed. The model provides a cost?effective tool for understanding and optimizing the in?furnace flow?thermo?chemical characteristics of the PCI process in full?scale blast furnaces.

Y. S. Shen; B. Y. Guo; A. B. Yu; P. Austin; P. Zulli

2010-01-01T23:59:59.000Z

460

An Integrated Approach to Quality Modelling Stefan Wagner and Florian Deissenboeck  

E-Print Network [OSTI]

quality that support engineers in dealing with a multitude of quality related issues. However, we stillAn Integrated Approach to Quality Modelling Stefan Wagner and Florian Deissenboeck Institut f,deissenb}@in.tum.de Abstract Software quality is described by various views using dif- ferent attributes and models. All

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Verification of the equilibrium and MHD stability codes within the Integrated Tokamak Modeling Task Force framework.  

E-Print Network [OSTI]

in order to avoid discrepancies in the results treatment. Often numerical codes use different post- and pre 2012, San Diego, US Validation of the numerical tools used for modeling of the fusion plasmaVerification of the equilibrium and MHD stability codes within the Integrated Tokamak Modeling Task

Vlad, Gregorio

462

Integrating Markov Chain Models and L-systems to Simulate the Architectural Development of Apple Trees  

E-Print Network [OSTI]

Integrating Markov Chain Models and L-systems to Simulate the Architectural Development of Apple the architectural development of apple trees is presented. The approach is based on using an L-systems framework. Results show that these models are able to represent the branching zones observed in apple trees at node

Paris-Sud XI, Université de

463

Integrated UML and modelica system modeling with ModelicaML in Eclipse  

Science Journals Connector (OSTI)

Complex products are increasingly consisting of both software and hardware components which are closely interacting. Thus, modeling tools and processes need to support co-design of software and hardware in an integrated way. Currently, UML is the dominant ... Keywords: SysML, UML, modelica, simulation, system modeling

Adrian Pop; David Akhvlediani; Peter Fritzson

2007-11-01T23:59:59.000Z

464

Integrated Design of Simulation Models for Passive Houses Petr Novak, Radek Sindelar  

E-Print Network [OSTI]

Integrated Design of Simulation Models for Passive Houses Petr Nov´ak, Radek Sindel´ar Christian. The use-case shows that the design of simulation models for passive houses can be user-friendly and feasible even for non-experts as it is based on a graphical tool that enables to draw a passive house floor

465

An integrated environmental modeling framework for performing Quantitative Microbial Risk Assessments  

Science Journals Connector (OSTI)

Standardized methods are often used to assess the likelihood of a human-health effect from exposure to a specified hazard, and inform opinions and decisions about risk management and communication. A Quantitative Microbial Risk Assessment (QMRA) is specifically ... Keywords: Integrated environmental modeling, Manure, Pathogens, QMRA, Risk assessment, Watershed modeling

Gene Whelan, Keewook Kim, Mitch A. Pelton, Jeffrey A. Soller, Karl J. Castleton, Marirosa Molina, Yakov Pachepsky, Richard Zepp

2014-05-01T23:59:59.000Z

466

Integrated biomechanical model of cells embedded in extracellular matrix  

E-Print Network [OSTI]

of cells, which in turn gives rise to the characteristic form for the organism. Morphogenesis is a multi-scale modeling problem that can be studied at the molecular, cellular, and tissue levels. Here, we study the problem of morphogenesis at the cellular...

Muddana, Hari Shankar

2009-05-15T23:59:59.000Z

467

Parameter-oriented Visualization of a Modelica Model with a Numerical Data Integration Feature  

Science Journals Connector (OSTI)

Abstract In model-based development, designers develop models of complex engineered systems from combinations of building blocks, and then simulate the system behavior. The design process is assisted by multi-domain system modeling and simulation tools. These tools should be able to allow users to understand and validate the simulated behavior in terms of parameters and their dependencies with effective use of quantitative information, such as simulation results, experiments, and catalog data, in the system model. This paper proposes a tool that displays the parameters and their dependencies in system models written in Modelica, and integrates these models with numerical data. The latter feature is useful for evaluating quantitative performance.

Hitoshi Komoto; Shinsuke Kondoh; Keijiro Masui; Akira Tezuka

2014-01-01T23:59:59.000Z

468

Power load forecasting using data mining and knowledge discovery technology  

Science Journals Connector (OSTI)

Considering the importance of the peak load to the dispatching and management of the electric system, the error of peak load is proposed in this paper as criteria to evaluate the effect of the forecasting model. This paper proposes a systemic framework that attempts to use data mining and knowledge discovery (DMKD) to pretreat the data. And a new model is proposed which combines artificial neural networks with data mining and knowledge discovery for electric load forecasting. With DMKD technology, the system not only could mine the historical daily loading which had the same meteorological category as the forecasting day to compose data sequence with highly similar meteorological features, but also could eliminate the redundant influential factors. Then an artificial neural network is constructed to predict according to its characteristics. Using this new model, it could eliminate the redundant information, accelerate the training speed of neural network and improve the stability of the convergence. Compared with single BP neural network, this new method can achieve greater forecasting accuracy.

Yongli Wang; Dongxiao Niu; Ling Ji

2011-01-01T23:59:59.000Z

469

A Process Model of Applicant Faking on Overt Integrity Tests  

E-Print Network [OSTI]

of empirically tested models or appropriate theoretical structures to explain the process (Griffith & McDaniel, 2006; Murphy, 2000). Moreover, there seems to be a limited understanding of possible outcomes associated with applicant faking..., Barrett, & Hogan, 2007; McFarland & Ryan, 2006; Morgeson et al., 2007). According to recent studies, approximately 30-50% of job applicants consciously try to elevate their scores (Donovan, Dwight, & Hurtz, 2003; Griffith et al., 2007)1. Faking...

Yu, Janie

2010-01-14T23:59:59.000Z

470

An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study  

SciTech Connect (OSTI)

This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

De Mello, Phillip; Lu, Ning; Makarov, Yuri V.

2011-01-17T23:59:59.000Z

471

Shape Changing and Accelerating Solitons in the Integrable Variable Mass Sine-Gordon Model  

SciTech Connect (OSTI)

The sine-Gordon model with a variable mass (VMSG) appears in many physical systems, ranging from the current through a nonuniform Josephson junction to DNA-promoter dynamics. Such models are usually nonintegrable with solutions found numerically or perturbatively. We construct a class of VMSG models, integrable at both the classical and the quantum levels with exact soliton solutions, which can accelerate and change their shape, width, and amplitude simulating realistic inhomogeneous systems at certain limits.

Kundu, Anjan [Theory Group, Saha Institute of Nuclear Physics, Calcutta (India)

2007-10-12T23:59:59.000Z

472

Integrated Deployment Model: A Comprehensive Approach to Transforming the Energy Economy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Integrated Deployment Model: Integrated Deployment Model: A Comprehensive Approach to Transforming the Energy Economy Mary Werner Technical Report NREL/TP-7A20-49230 November 2010 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 Integrated Deployment Model: A Comprehensive Approach to Transforming the Energy Economy Mary Werner Prepared under Task No. IDPS.9010 Technical Report NREL/TP-7A20-49230 November 2010 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government.

473

NCAR WRF-based data assimilation and forecasting systems for wind energy applications power  

E-Print Network [OSTI]

NCAR WRF-based data assimilation and forecasting systems for wind energy applications power Yuewei of these modeling technologies w.r.t. wind energy applications. Then I'll discuss wind farm

Kim, Guebuem

474

A study of outliers in the exponential smoothing approach to forecasting  

Science Journals Connector (OSTI)

Outliers in time series have the potential to affect parameter estimates and forecasts when using exponential smoothing. The aim of this study is to show the way in which important types of outliers can be incorporated into linear innovations state space models for exponential smoothing methods. The types of outliers include an additive outlier, a level shift, and a transitory change. The general innovations state space model and a special case which encompasses the common linear exponential smoothing methods are examined. A method for identifying outliers using innovations state space models is proposed. This method is investigated using both simulations and applications to real time series. The impact of an outlier’s location on the forecasts and the estimation of parameters is examined. The forecasts from outlier and basic non-outlier models are compared. An automatic method is found to result in improved forecasts for both the simulated and real data.

Anne B. Koehler; Ralph D. Snyder; J. Keith Ord; Adrian Beaumont

2012-01-01T23:59:59.000Z

475

The Operational Implementation of a Great Lakes Wave Forecasting System at NOAA/NCEP  

Science Journals Connector (OSTI)

The development of a Great Lakes wave forecasting system at NOAA’s National Centers for Environmental Prediction (NCEP) is described. The system is an implementation of the WAVEWATCH III model, forced with atmospheric data from NCEP’s regional ...

Jose-Henrique G. M. Alves; Arun Chawla; Hendrik L. Tolman; David Schwab; Gregory Lang; Greg Mann

2014-12-01T23:59:59.000Z

476

Machine Learning Enhancement of Storm-Scale Ensemble Probabilistic Quantitative Precipitation Forecasts  

E-Print Network [OSTI]

Machine Learning Enhancement of Storm-Scale Ensemble Probabilistic Quantitative Precipitation uncertainty. Machine learning methods can produce calibrated probabilistic forecasts from the raw ensemble and machine learning are working to address these challenges. Numerical weather prediction (NWP) models

Xue, Ming

477

A Long Term Load Forecasting of an Indian Grid for Power System Planning  

Science Journals Connector (OSTI)

A time-series load modelling and load forecasting using neuro-fuzzy techniques were presented...7]. In this method, energy data of several past years is used to ... . ANN structure of ANFIS can capture the power ...

R. Behera; B. B. Pati; B. P. Panigrahi

2014-12-01T23:59:59.000Z

478

Comparison of long–term forecasting of June–August rainfall over changjiang–huaihe valley  

Science Journals Connector (OSTI)

In terms of an Artificial Neural Network (ANN) established is a long-term prediction model for June–August flood/drought in the Changjiang-Huaihe Basins and a regression forecasting expression is formulated wi...

Jin Long; Luo Ying; Lin Zhenshan

1997-01-01T23:59:59.000Z

479

Wintertime sub-kilometer numerical forecasts of near-surface variables in the Canadian Rocky Mountains  

Science Journals Connector (OSTI)

Numerical Weather Prediction (NWP) systems operational at many national centers are nowadays used at kilometer scale. The next generation of NWP models will provide forecasts at sub-kilometrer scale. Large impacts are expected in mountainous ...

Vincent Vionnet; Stéphane Bélair; Claude Girard; André Plante

480

Wind Speeds at Heights Crucial for Wind Energy: Measurements and Verification of Forecasts  

Science Journals Connector (OSTI)

Wind speed measurements from one year from meteorological towers and wind turbines at heights between 20 and 250 m for various European sites are analyzed and are compared with operational short-term forecasts of the global ECMWF model. The ...

Susanne Drechsel; Georg J. Mayr; Jakob W. Messner; Reto Stauffer

2012-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "integrated forecasting model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Energy Demand Forecasting in China Based on Dynamic RBF Neural Network  

Science Journals Connector (OSTI)

A dynamic radial basis function (RBF) network model is proposed for energy demand forecasting in this paper. Firstly, we ... detail. At last, the data of total energy demand in China are analyzed and experimental...

Dongqing Zhang; Kaiping Ma; Yuexia Zhao

2011-01-01T23:59:59.000Z

482

Weather Forecast Data an Important Input into Building Management Systems  

E-Print Network [OSTI]

Lewis Poulin Implementation and Operational Services Section Canadian Meteorological Centre, Dorval, Qc National Prediction Operations Division ICEBO 2013, Montreal, Qc October 10 2013 Version 2013-09-27 Weather Forecast Data An Important... and weather information ? Numerical weather forecast production 101 ? From deterministic to probabilistic forecasts ? Some MSC weather forecast (NWP) datasets ? Finding the appropriate data for the appropriate forecast ? Preparing for probabilistic...

Poulin, L.

2013-01-01T23:59:59.000Z

483

NREL: Transmission Grid Integration - Publications  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications Publications Want updates about future transmission grid integration webinars and publications? Join our mailing list. NREL has an extensive collection of publications related to transmission integration research. Explore the resources below to learn more. Selected Project Publications Read selected publications related to these transmission integration projects: Western Wind and Solar Integration Study Eastern Renewable Generation Integration Study Oahu Wind Integration and Transmission Study Flexible Energy Scheduling Tool for Integration of Variable generation (FESTIV) Active power controls Forecasting Grid Simulation. NREL Publications Database NREL's publications database offers a variety of documents related to transmission integration that were written by NREL staff and

484

Simulations of cirrus clouds using an explicit cloud model: integrating ARM  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Simulations of cirrus clouds using an explicit cloud model: integrating ARM Simulations of cirrus clouds using an explicit cloud model: integrating ARM water vapor and forcing data for analysis of cirrus formation and evolution Comstock, Jennifer Pacific Northwest National Laboratory Lin, Ruei-Fong NASA/Goddard Space Flight Center Starr, David NASA/Goddard Space Flight Center Yang, Ping Texas A&M Category: Modeling Understanding the atmospheric conditions required to initiate cirrus formation and produce observed microphysical properties is crucial to improving the representation of cirrus clouds in climate models. Ice formation in cirrus generally occurs at cold temperatures (below -30 ï‚°C) and can take the form of either homogeneous or heterogeneous nucleation. The ice supersaturation required for ice formation is smaller for

485

CONTROL-ORIENTED MODEL OF AN INTEGRATED FUEL CELL STACK AND FUEL  

E-Print Network [OSTI]

CONTROL-ORIENTED MODEL OF AN INTEGRATED FUEL CELL STACK AND FUEL PROCESSOR SYSTEM 1 Jay T feed to the PEM-FC. Cost and performance requirements of the total powertrain typically lead to highly and conditions. Keywords: Fuel Cell, Fuel Processor, Multivariable Feedback, Linear Control, Partial Oxidation 1

Stefanopoulou, Anna

486

Jan 16 Conceptual models of ecological systems Why is Integration Needed in Ecology?  

E-Print Network [OSTI]

Jan 16 Conceptual models of ecological systems #12;Why is Integration Needed in Ecology? Great advances have been made by dividing ecology into subdisciplines. But too much focus on subdisciplines has also hindered ecology · too little study of the interface between disciplines · tended to narrow focus

Hansen, Andrew J.

487

A long-term investment planning model for mixed energy infrastructure integrated with renewable  

E-Print Network [OSTI]

A long-term investment planning model for mixed energy infrastructure integrated with renewable energy Jinxu Ding and Arun Somani Department of Electrical and Computer Engineering Iowa State University Ames, IA 50011 Email: {jxding,arun}@iastate.edu Abstract--The current energy infrastructure heavily

488

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

H Tables H Tables Appendix H Comparisons With Other Forecasts, and Performance of Past IEO Forecasts for 1990, 1995, and 2000 Forecast Comparisons Three organizations provide forecasts comparable with those in the International Energy Outlook 2005 (IEO2005). The International Energy Agency (IEA) provides “business as usual” projections to the year 2030 in its World Energy Outlook 2004; Petroleum Economics, Ltd. (PEL) publishes world energy forecasts to 2025; and Petroleum Industry Research Associates (PIRA) provides projections to 2015. For this comparison, 2002 is used as the base year for all the forecasts, and the comparisons extend to 2025. Although IEA’s forecast extends to 2030, it does not publish a projection for 2025. In addition to forecasts from other organizations, the IEO2005 projections are also compared with those in last year’s report (IEO2004). Because 2002 data were not available when IEO2004 forecasts were prepared, the growth rates from IEO2004 are computed from 2001.

489

Funding Opportunity Announcement for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

490

Upcoming Funding Opportunity for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

491

Huge market forecast for linear LDPE  

Science Journals Connector (OSTI)

Huge market forecast for linear LDPE ... It now appears that the success of the new technology, which rests largely on energy and equipment cost savings, could be overwhelming. ...

1980-08-25T23:59:59.000Z

492

Annual Energy Outlook 1998 Forecasts - Preface  

Gasoline and Diesel Fuel Update (EIA)

1998 With Projections to 2020 1998 With Projections to 2020 Annual Energy Outlook 1999 Report will be Available on December 9, 1998 Preface The Annual Energy Outlook 1998 (AEO98) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO98 reference case. The next section, “Legislation and Regulations,” describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. “Issues in Focus” discusses three current energy issues—electricity restructuring, renewable portfolio standards, and carbon emissions. It is followed by the analysis

493

Incorporating Forecast Uncertainty in Utility Control Center  

SciTech Connect (OSTI)

Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

2014-07-09T23:59:59.000Z

494

NOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future)  

E-Print Network [OSTI]

conditions for up to 5 days in the future. These forecasts are run twice daily, and you can step through are generated every 6 hours and you can step backward in hourly increments to view conditions over the previousNOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future) and Nowcasts

495

FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake Erie  

E-Print Network [OSTI]

. The in- crease in computer power in recent years and advances in numerical mesoscale models of both ocean September 1998) ABSTRACT This article has two purposes. The first is to describe how the Great Lakes Coastal. This includes the numerical Princeton Ocean Model (POM), observed winds from surface meteorological stations

496

Development of short-term forecast quality for new offshore wind farms  

Science Journals Connector (OSTI)

As the rapid wind power build-out continues, a large number of new wind farms will come online but forecasters and forecasting algorithms have little experience with them. This is a problem for statistical short term forecasts, which must be trained on a long record of historical power production – exactly what is missing for a new farm. Focus of the study was to analyse development of the offshore wind power forecast (WPF) quality from beginning of operation up to one year of operational experience. This paper represents a case study using data of the first German offshore wind farm "alpha ventus" and first German commercial offshore wind farm "Baltic1". The work was carried out with measured data from meteorological measurement mast FINO1, measured power from wind farms and numerical weather prediction (NWP) from the German Weather Service (DWD). This study facilitates to decide the length of needed time series and selection of forecast method to get a reliable WPF on a weekly time axis. Weekly development of WPF quality for day-ahead WPF via different models is presented. The models are physical model; physical model extended with a statistical correction (MOS) and artificial neural network (ANN) as a pure statistical model. Selforganizing map (SOM) is investigated for a better understanding of uncertainties of forecast error.

M Kurt; B Lange

2014-01-01T23:59:59.000Z

497

Claudio Schepke: Online Parallel Mesh Refinement for Climatological Applications Weather forecasts for long periods of time have emerged as increasingly important.  

E-Print Network [OSTI]

Claudio Schepke: Online Parallel Mesh Refinement for Climatological Applications Weather forecasts, this presentation discusses how to explore parallelism at different levels for climatological models, like OLAM

Wichmann, Felix

498

Annual Energy Outlook Forecast Evaluation - Table 1. Forecast Evaluations:  

Gasoline and Diesel Fuel Update (EIA)

Average Absolute Percent Errors from AEO Forecast Evaluations: Average Absolute Percent Errors from AEO Forecast Evaluations: 1996 to 2000 Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Variable 1996 Evaluation: AEO82 to AEO93 1997 Evaluation: AEO82 to AEO97 1998 Evaluation: AEO82 to AEO98 1999 Evaluation: AEO82 to AEO99 2000 Evaluation: AEO82 to AEO2000 Consumption Total Energy Consumption 1.8 1.6 1.7 1.7 1.8 Total Petroleum Consumption 3.2 2.8 2.9 2.8 2.9 Total Natural Gas Consumption 6.0 5.8 5.7 5.6 5.6 Total Coal Consumption 2.9 2.7 3.0 3.2 3.3 Total Electricity Sales 1.8 1.6 1.7 1.8 2.0 Production Crude Oil Production 5.1 4.2 4.3 4.5 4.5

499

Optimal combined wind power forecasts using exogeneous variables  

E-Print Network [OSTI]

Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

500

A New Method for History Matching and Forecasting Shale Gas/Oil Reservoir Production Performance with Dual and Triple Porosity Models  

E-Print Network [OSTI]

Different methods have been proposed for history matching production of shale gas/oil wells which are drilled horizontally and usually hydraulically fractured with multiple stages. These methods are simulation, analytical models, and empirical...

Samandarli, Orkhan

2012-10-19T23:59:59.000Z