Powered by Deep Web Technologies
Note: This page contains sample records for the topic "module generates forecasts" 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

System Demonstration Multilingual Weather Forecast Generation System  

E-Print Network (OSTI)

System Demonstration Multilingual Weather Forecast Generation System Tianfang Yao DongmoZhang Qian (Multilingual Weather Forecasts Assistant) system will be demonstrated. It is developed to generate the multilingual text of the weather forecasts automatically. The raw data from the weather observation can be used

2

SLCA/IP Hydro Generation Estimates Month Forecast Generation  

NLE Websites -- All DOE Office Websites (Extended Search)

42014 15:46 SLCAIP Hydro Generation Estimates Month Forecast Generation less losses (kWh) Less Proj. Use (kWh) Net Generation (kWh) SHP Deliveries (kWh) Firming Purchases (kWh)...

3

SLCA/IP Hydro Generation Estimates Month Forecast Generation  

NLE Websites -- All DOE Office Websites (Extended Search)

13 16:39 SLCAIP Hydro Generation Estimates Month Forecast Generation less losses (kWh) Less Proj. Use (kWh) Net Generation (kWh) SHP Deliveries (kWh) Firming Purchases (kWh)...

4

Computer Generation of Marine Weather Forecast Text  

Science Conference Proceedings (OSTI)

MARWORDS is a natural language text generation system which has been developed to synthesize marine forecasts for the Davis Strait area in Northern Canada. It uses standard manually produced predictions of wind speed, air temperature, and other ...

E. Goldberg; R. Kittredge; A. Polgučre

1988-08-01T23:59:59.000Z

5

SLCA/IP Hydro Generation Estimates Month Forecast Generation  

NLE Websites -- All DOE Office Websites (Extended Search)

5/2013 9:06 5/2013 9:06 SLCA/IP Hydro Generation Estimates Month Forecast Generation less losses (kWh) Less Proj. Use (kWh) Net Generation (kWh) SHP Deliveries (kWh) Firming Purchases (kWh) Generation above SHP Level (kWH) 2013-Oct 232,469,911 13,095,926 219,373,985 398,608,181 192,676,761 - 2013-Nov 211,770,451 2,989,074 208,781,376 408,041,232 214,204,345 - 2013-Dec 252,579,425 3,106,608 249,472,817 455,561,848 221,545,708 - 2014-Jan 337,006,077 3,105,116 333,900,962 463,462,717 139,278,887 -

6

Model documentation: electricity market module. [15 year forecasts  

SciTech Connect

This report documents the electricity market model. This model is a component of the Intermediate Future Forecasting System (IFFS), the energy market model used to provide projections of energy markets up to 15 years into the future. The electricity market model was developed by the Supply Analysis and Integration Branch as part of building the larger system. This report is written for an audience consisting of mathematical economists, statisticians, operations research analysts, and utility planners. This report contains an overview and a mathematical specification of the electricity market module. It includes a description of the model logic and the individual subroutines in the computer code. A companion document Intermediate Future Forecasting System: Executive Summary (DOE/EIA-430) provides an overview of the components in IFFS and their linkages. 22 figures, 2 tables.

Sanders, R.C.; Murphy, F.H.

1984-12-01T23:59:59.000Z

7

MLWFA: A Multilingual Weather Forecast Text Generation Tianfang YAO Dongmo ZHANG Qian WANG  

E-Print Network (OSTI)

MLWFA: A Multilingual Weather Forecast Text Generation System1 Tianfang YAO Dongmo ZHANG Qian WANG generation; Weather forecast generation system Abstract In this demonstration, we present a system for multilingual text generation in the weather forecast domain. Multilingual Weather Forecast Assistant (MLWFA

Wu, Dekai

8

Lessons from Deploying NLG Technology for Marine Weather Forecast Text Generation  

E-Print Network (OSTI)

Lessons 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 for producing 150 draft forecasts per day, which are then post-edited by forecasters before being released

Sripada, Yaji

9

Survey of Variable Generation Forecasting in the West: August 2011 - June 2012  

DOE Green Energy (OSTI)

This report surveyed Western Interconnection Balancing Authorities regarding their implementation of variable generation forecasting, the lessons learned to date, and recommendations they would offer to other Balancing Authorities who are considering variable generation forecasting. Our survey found that variable generation forecasting is at an early implementation stage in the West. Eight of the eleven Balancing Authorities interviewed began forecasting in 2008 or later. It also appears that less than one-half of the Balancing Authorities in the West are currently utilizing variable generation forecasting, suggesting that more Balancing Authorities in the West will engage in variable generation forecasting should more variable generation capacity be added.

Porter, K.; Rogers, J.

2012-04-01T23:59:59.000Z

10

Post-processing of ensemble weather forecasts using a stochastic weather generator  

Science Conference Proceedings (OSTI)

This study proposes a new statistical method for post-processing ensemble weather forecasts using a stochastic weather generator. Key parameters of the weather generator were linked to the ensemble forecast means for both precipitation and ...

Jie Chen; François P. Brissette; Zhi Li

11

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

12

SLCA/IP Hydro Generation Estimates Month Forecast Generation  

NLE Websites -- All DOE Office Websites (Extended Search)

Less Proj. Use (kWh) Net Generation (kWh) SHP Deliveries (kWh) Firming Purchases (kWh) Generation above SHP Level (kWH) 2012-Oct 253,769,055 13,095,926 240,673,129 398,608,181...

13

Mesoscale Forecasts Generated from Operational Numerical Weather-Prediction Model Output  

Science Conference Proceedings (OSTI)

A technique called Model Output Enhancement (MOE) has been developed for the generation and display of mesoscale weather forecasts. The MOE technique derives mesoscale or high-resolution (order of 1 km) weather forecasts from synoptic-scale ...

John G. W. Kelley; Joseph M. Russo; Toby N. Carlson; J. Ronald Eyton

1988-01-01T23:59:59.000Z

14

Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets  

E-Print Network (OSTI)

In current restructured wholesale power markets, the short length of time series for prices makes it difficult to use empirical price data to test existing price forecasting tools and to develop new price forecasting tools. This study therefore proposes a two-stage approach for generating simulated price scenarios based on the available price data. The first stage consists of an Autoregressive Moving Average (ARMA) model for determining scenarios of cleared demands and scheduled generator outages (D&O), and a moment-matching method for reducing the number of D&O scenarios to a practical scale. In the second stage, polynomials are fitted between D&O and wholesale power prices in order to obtain price scenarios for a specified time frame. Time series data from the Midwest ISO (MISO) are used as a test system to validate the proposed approach. The simulation results indicate that the proposed approach is able to generate price scenarios for distinct seasons with empirically realistic characteristics.

Qun Zhou; Leigh Tesfatsion; Chen-Ching Liu

2009-01-01T23:59:59.000Z

15

EVALUATION OF PV GENERATION CAPICITY CREDIT FORECAST ON DAY-AHEAD UTILITY MARKETS  

E-Print Network (OSTI)

EVALUATION OF PV GENERATION CAPICITY CREDIT FORECAST ON DAY-AHEAD UTILITY MARKETS Richard Perez of the NDFD-based solar radiation forecasts for several climatically distinct locations, the evaluation is now continued by testing the forecasts' end-use operational accuracy, focusing on their ability to accurately

Perez, Richard R.

16

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty  

SciTech Connect

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

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

2013-12-18T23:59:59.000Z

17

PSCAD Modules Representing PV Generator  

SciTech Connect

Photovoltaic power plants (PVPs) have been growing in size, and the installation time is very short. With the cost of photovoltaic (PV) panels dropping in recent years, it can be predicted that in the next 10 years the contribution of PVPs to the total number of renewable energy power plants will grow significantly. In this project, the National Renewable Energy Laboratory (NREL) developed a dynamic modeling of the modules to be used as building blocks to develop simulation models of single PV arrays, expanded to include Maximum Power Point Tracker (MPPT), expanded to include PV inverter, or expanded to cover an entire PVP. The focus of the investigation and complexity of the simulation determines the components that must be included in the simulation. The development of the PV inverter was covered in detail, including the control diagrams. Both the current-regulated voltage source inverter and the current-regulated current source inverter were developed in PSCAD. Various operations of the PV inverters were simulated under normal and abnormal conditions. Symmetrical and unsymmetrical faults were simulated, presented, and discussed. Both the three-phase analysis and the symmetrical component analysis were included to clarify the understanding of unsymmetrical faults. The dynamic model validation was based on the testing data provided by SCE. Testing was conducted at SCE with the focus on the grid interface behavior of the PV inverter under different faults and disturbances. The dynamic model validation covers both the symmetrical and unsymmetrical faults.

Muljadi, E.; Singh, M.; Gevorgian, V.

2013-08-01T23:59:59.000Z

18

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty  

Science Conference Proceedings (OSTI)

This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

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

2013-07-25T23:59:59.000Z

19

Thirty-Year Solid Waste Generation Maximum and Minimum Forecast for SRS  

SciTech Connect

This report is the third phase (Phase III) of the Thirty-Year Solid Waste Generation Forecast for Facilities at the Savannah River Site (SRS). Phase I of the forecast, Thirty-Year Solid Waste Generation Forecast for Facilities at SRS, forecasts the yearly quantities of low-level waste (LLW), hazardous waste, mixed waste, and transuranic (TRU) wastes generated over the next 30 years by operations, decontamination and decommissioning and environmental restoration (ER) activities at the Savannah River Site. The Phase II report, Thirty-Year Solid Waste Generation Forecast by Treatability Group (U), provides a 30-year forecast by waste treatability group for operations, decontamination and decommissioning, and ER activities. In addition, a 30-year forecast by waste stream has been provided for operations in Appendix A of the Phase II report. The solid wastes stored or generated at SRS must be treated and disposed of in accordance with federal, state, and local laws and regulations. To evaluate, select, and justify the use of promising treatment technologies and to evaluate the potential impact to the environment, the generic waste categories described in the Phase I report were divided into smaller classifications with similar physical, chemical, and radiological characteristics. These smaller classifications, defined within the Phase II report as treatability groups, can then be used in the Waste Management Environmental Impact Statement process to evaluate treatment options. The waste generation forecasts in the Phase II report includes existing waste inventories. Existing waste inventories, which include waste streams from continuing operations and stored wastes from discontinued operations, were not included in the Phase I report. Maximum and minimum forecasts serve as upper and lower boundaries for waste generation. This report provides the maximum and minimum forecast by waste treatability group for operation, decontamination and decommissioning, and ER activities.

Thomas, L.C.

1994-10-01T23:59:59.000Z

20

Using Evolutionary Programming to Generate Skillful Extreme Value Probabilistic Forecasts  

Science Conference Proceedings (OSTI)

A new method for producing large member ensemble forecasts, using a variation of Evolutionary Programming (EP), is presented. A series of increasingly complex datasets are used to demonstrate the method and its potential utility. First, EP ...

Paul J. Roebber

Note: This page contains sample records for the topic "module generates forecasts" 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

Using Evolutionary Programming to Generate Skillful Extreme Value Probabilistic Forecasts  

Science Conference Proceedings (OSTI)

A new method for producing large member ensemble forecasts, using a variation of evolutionary programming (EP), is presented. A series of increasingly complex datasets are used to demonstrate the method and its potential utility. First, EP ...

Paul J. Roebber

2013-09-01T23:59:59.000Z

22

An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study  

SciTech Connect

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

23

Comparison of Methods Used to Generate Probabilistic Quantitative Precipitation Forecasts over South America  

Science Conference Proceedings (OSTI)

In this work, the quality of several probabilistic quantitative precipitation forecasts (PQPFs) is examined. The analysis is focused over South America during a 2-month period in the warm season. Several ways of generating and calibrating the ...

Juan Ruiz; Celeste Saulo; Eugenia Kalnay

2009-02-01T23:59:59.000Z

24

A Weather and Climate Enterprise Strategic Implementation Plan for Generating and Communicating Forecast Uncertainty Information  

Science Conference Proceedings (OSTI)

The American Meteorological Society (AMS) Weather and Climate Enterprise Strategic Implementation Plan for Generating and Communicating Forecast Uncertainty (the Plan) is summarized. The Plan (available on the AMS website at www.ametsoc.org/boardpges/cwce/...

Paul A. Hirschberg; Elliot Abrams; Andrea Bleistein; William Bua; Luca Delle Monache; Thomas W. Dulong; John E. Gaynor; Bob Glahn; Thomas M. Hamill; James A. Hansen; Douglas C. Hilderbrand; Ross N. Hoffman; Betty Hearn Morrow; Brenda Philips; John Sokich; Neil Stuart

2011-12-01T23:59:59.000Z

25

Integration of Variable Generation Forecasting into System Operations: Current Practices and Future Requirements  

Science Conference Proceedings (OSTI)

This project update provides the first output of the EPRI Bulk Renewable Integration Program Project P173-010, “Integration of Variable Generation Forecasts into System Operations.” This project, begun in 2013, aims to improve existing methods utilities/independent system operators (ISOs) use to integrate forecasts into system operations and develop new methods. This year’s goal was to identify current practices and future requirements. This was done by interacting with a wide ...

2013-12-11T23:59:59.000Z

26

Forecasting Techniques The Use of Hourly Model-Generated Soundings to Forecast Mesoscale Phenomena. Part I: Initial Assessment in Forecasting Warm-Season Phenomena  

Science Conference Proceedings (OSTI)

Since late 1995, NCEP has made available to forecasters hourly model guidance at selected sites in the form of vertical profiles of various forecast fields. These profiles provide forecasters with increased temporal resolution and greater ...

Robert E. Hart; Gregory S. Forbes; Richard H. Grumm

1998-12-01T23:59:59.000Z

27

The Economic Value of Temperature Forecasts in Electricity Generation  

Science Conference Proceedings (OSTI)

Every day, the U.S. electricity-generating industry decides how to meet the electricity demand anticipated over the next 24 h. Various generating units are available to meet the demand, and each unit may have its own production lead time, start-...

Thomas J. Teisberg; Rodney F. Weiher; Alireza Khotanzad

2005-12-01T23:59:59.000Z

28

A Framework of Incorporating Spatio-temporal Forecast in Look-ahead Grid Dispatch with Photovoltaic Generation  

E-Print Network (OSTI)

Increasing penetration of stochastic photovoltaic (PV) generation into the electric power system poses significant challenges to system operators. In the thesis, we evaluate the spatial and temporal correlations of stochastic PV generation at multiple sites. Given the unique spatial and temporal correlation of PV generation, an optimal data-driven forecast model for short-term PV power is proposed. This model leverages both spatial and temporal correlations among neighboring solar sites, and is shown to have improved performance compared with conventional persistent model. The tradeoff between communication cost and improved forecast quality is studied using realistic data sets collected from California and Colorado. n IEEE 14 bus system test case is used to quantify the value of improved forecast quality through the reduction of system dispatch cost. The Modified spatio-temporal forecast model which has the least forecast PV overestimate percentage shows the best performance in the dispatch cost reduction.

Yang, Chen

2013-05-01T23:59:59.000Z

29

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

30

Thirty-year solid waste generation forecast for facilities at SRS  

SciTech Connect

The information supplied by this 30-year solid waste forecast has been compiled as a source document to the Waste Management Environmental Impact Statement (WMEIS). The WMEIS will help to select a sitewide strategic approach to managing present and future Savannah River Site (SRS) waste generated from ongoing operations, environmental restoration (ER) activities, transition from nuclear production to other missions, and decontamination and decommissioning (D&D) programs. The EIS will support project-level decisions on the operation of specific treatment, storage, and disposal facilities within the near term (10 years or less). In addition, the EIS will provide a baseline for analysis of future waste management activities and a basis for the evaluation of the specific waste management alternatives. This 30-year solid waste forecast will be used as the initial basis for the EIS decision-making process. The Site generates and manages many types and categories of waste. With a few exceptions, waste types are divided into two broad groups-high-level waste and solid waste. High-level waste consists primarily of liquid radioactive waste, which is addressed in a separate forecast and is not discussed further in this document. The waste types discussed in this solid waste forecast are sanitary waste, hazardous waste, low-level mixed waste, low-level radioactive waste, and transuranic waste. As activities at SRS change from primarily production to primarily decontamination and decommissioning and environmental restoration, the volume of each waste s being managed will change significantly. This report acknowledges the changes in Site Missions when developing the 30-year solid waste forecast.

Not Available

1994-07-01T23:59:59.000Z

31

Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

Science Conference Proceedings (OSTI)

In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Chakrabarti, Bhujanga B.; Subbarao, Krishnappa; Loutan, Clyde; Guttromson, Ross T.

2010-04-20T23:59:59.000Z

32

AEOP2011:Electricity Generation Capacity by Electricity Market Module  

Open Energy Info (EERE)

AEOP2011:Electricity Generation Capacity by Electricity Market Module AEOP2011:Electricity Generation Capacity by Electricity Market Module Region and Source Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 97, and contains only the reference case. The dataset uses billion kilowatthours. The data is broken down into Texas regional entity, Florida reliability coordinating council, Midwest reliability council and Northeast power coordination council. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords AEO Electricity electricity market module region generation capacity Data application/vnd.ms-excel icon AEO2011: Electricity Generation Capacity by Electricity Market Module Region and Source- Reference Case (xls, 10.6 KiB)

33

AEO2011: Electricity Generation by Electricity Market Module...  

Open Energy Info (EERE)

Generation by Electricity Market Module Region and Source

34

AEO2011: Electricity Generation by Electricity Market Module Region and  

Open Energy Info (EERE)

Generation by Electricity Market Module Region and Generation by Electricity Market Module Region and Source Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 96, and contains only the reference case. The dataset uses billion kilowatthours. The data is broken down into texas regional entity, Florida reliability coordinating council, midwest reliability council and northeast power coordination council. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Electricity generation Data application/vnd.ms-excel icon AEO2011: Electricity Generation by Electricity Market Module Region and Source- Reference Case (xls, 400.2 KiB) Quality Metrics

35

Predicting daily streamflow using rainfall forecasts, a simple loss module and unit hydrographs: Two Brazilian catchments  

Science Conference Proceedings (OSTI)

The performance of a simple, spatially-lumped, rainfall-streamflow model is compared with that of a more complex, spatially-distributed model. In terms of two model-fit statistics it is shown that for two catchments in Brazil (about 30,000km^2 and 34,000km^2) ... Keywords: Brazil, Hydropower, Rainfall forecasts, River Paraná, Streamflow forecasts, Unit hydrographs

I. G. Littlewood; R. T. Clarke; W. Collischonn; B. F. W. Croke

2007-09-01T23:59:59.000Z

36

Forecasting overview  

E-Print Network (OSTI)

Forecasting is required in many situations: deciding whether to build another power generation plant in the next five years requires forecasts of future demand; scheduling staff in a call centre next week requires forecasts of call volume; stocking an inventory requires forecasts of stock requirements. Forecasts can be required several years in advance (for the case of capital investments), or only a few minutes beforehand (for telecommunication routing). Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. Some things are easier to forecast than others. The time of the sunrise tomorrow morning can be forecast very precisely. On the other hand, currency exchange rates are very difficult to forecast with any accuracy. The predictability of an event or a quantity depends on how well we understand the factors that contribute to it, and how much unexplained variability is involved. Forecasting situations vary widely in their time horizons, factors determining actual outcomes, types of data patterns, and many other aspects. Forecasting methods can be very simple such as using the most recent observation as a forecast (which is called the “naďve method”), or highly complex such as neural nets and econometric systems of simultaneous equations. The

Rob J Hyndman

2009-01-01T23:59:59.000Z

37

Incorporating Wind Generation Forecast Uncertainty into Power System Operation, Dispatch, and Unit Commitment Procedures  

DOE Green Energy (OSTI)

In this paper, an approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the "flying-brick" technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors.

Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Subbarao, Krishnappa

2010-10-19T23:59:59.000Z

38

Incorporating Uncertainty of Wind Power Generation Forecast into Power System Operation, Dispatch, and Unit Commitment Procedures  

Science Conference Proceedings (OSTI)

An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the 'flying-brick' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through EMS integration illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems in control rooms.

Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian; Huang, Zhenyu; Subbarao, Krishnappa

2011-06-23T23:59:59.000Z

39

A review of agent-based models for forecasting the deployment of distributed generation in energy systems  

Science Conference Proceedings (OSTI)

Agent-based models are seeing increasing use in the study of distributed generation (DG) deployment. Researchers and decision makers involved in the implementation of DG have been lacking a concise overview of why they should consider using agent-based ... Keywords: agent-based modeling, consumer behavior, distributed generation, energy forecasting, product deployment

Jason G. Veneman; M. A. Oey; L. J. Kortmann; F. M. Brazier; L. J. de Vries

2011-06-01T23:59:59.000Z

40

Imaging Collagen Orientation Using Polarization-Modulated Second Harmonic Generation  

Science Conference Proceedings (OSTI)

We use polarization-modulated second harmonic generation to image fiber orientation in collagen tissues, with an axial resolution of about 10 {micro}m and a transverse resolution of up to 1 {micro}m. A linearly polarized ultra-short pulse (200 fs) Ti:Sapphire laser beam is modulated using an electro-optic modulator and quarter-wave plate combination and focused onto a translation stage mounted sample using a microscope objective. The generated second harmonic light is collected using a photomultiplier tube and demodulated using phase sensitive detection to obtain signal intensity and fiber orientation information. In order to obtain second harmonic generation images of different types of collagen organization, we analyze several different tissues, including rat-tail tendon, mouse aorta, mouse fibrotic liver, and porcine skin. We can use our technique to image fibrotic tissue in histological sections of damaged liver and to identify burned tissue in porcine skin to a depth of a few hundred microns. Polarization-modulated second harmonic generation potentially could be a useful clinical technique for diagnosing collagen related disease or damage, especially in the skin.

Stoller, P; Celliers, P M; Reiser, K M; Rubenchik, A M

2002-01-10T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Automatic generation of weather forecast texts using comprehensive probabilistic generation-space models  

Science Conference Proceedings (OSTI)

Two important recent trends in natural language generation are (i) probabilistic techniques and (ii) comprehensive approaches that move away from traditional strictly modular and sequential models. This paper reports experiments in which pCRU ...

Anja Belz

2008-10-01T23:59:59.000Z

42

Waste generation forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1995-FY 2002, September 1994 revision  

Science Conference Proceedings (OSTI)

A comprehensive waste-forecasting task was initiated in FY 1991 to provide a consistent, documented estimate of the volumes of waste expected to be generated as a result of U.S. Department of Energy-Oak Ridge Operations (DOE-ORO) Environmental Restoration (ER) OR-1 Project activities. Continual changes in the scope and schedules for remedial action (RA) and decontamination and decommissioning (D&D) activities have required that an integrated data base system be developed that can be easily revised to keep pace with changes and provide appropriate tabular and graphical output. The output can then be analyzed and used to drive planning assumptions for treatment, storage, and disposal (TSD) facilities. The results of this forecasting effort and a description of the data base developed to support it are provided herein. The initial waste-generation forecast results were compiled in November 1991. Since the initial forecast report, the forecast data have been revised annually. This report reflects revisions as of September 1994.

Not Available

1994-12-01T23:59:59.000Z

43

Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

SciTech Connect

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

2010-01-01T23:59:59.000Z

44

Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

SciTech Connect

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system “breaking points”, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

2010-09-01T23:59:59.000Z

45

Generation of Coherent X-Ray Radiation through Modulation Compression  

Science Conference Proceedings (OSTI)

In this paper, we propose a scheme to generate tunable coherent X-ray radiation for future light source applications. This scheme uses an energy chirped electron beam, a laser modulator, a laser chirper and two bunch compressors to generate a prebunched kilo-Ampere current electron beam from a few tens Ampere electron beam out of a linac. The initial modulation energy wavelength can be compressed by a factor of 1 + h{sub b}R{sub 56}{sup a} in phase space, where h{sub b} is the energy bunch length chirp introduced by the laser chirper, R{sub 56}{sup a} is the momentum compaction factor of the first bunch compressor. As an illustration, we present an example to generate more than 400 MW, 170 attoseconds pulse, 1 nm coherent X-ray radiation using a 60 A electron beam out of the linac and 200 nm laser seed. Both the final wavelength and the radiation pulse length in the proposed scheme are tunable by adjusting the compression factor and the laser parameters.

Qiang, Ji; /LBL, Berkeley; Wu, Juhao; /SLAC

2012-06-12T23:59:59.000Z

46

Application of field-modulated generator systems to dispersed solar thermal electric generation  

DOE Green Energy (OSTI)

A Parabolic Dish-Electric Transport concept for dispersed solar thermal generation is considered. In this concept the power generated by 15 kWe Solar Generation Units is electrically collected in a large plant. Various approaches are possible for the conversion of mechanical shaft output of the heat engines to electricity. This study focuses on the Application of Field Modulated Generation System (FMGS) for that purpose. Initially the state-of-the-art of FMGS is presented, and the application of FMGS to dispersed solar thermal electric generation is investigated. This is followed by the definition of the control and monitoring requirements for solar generation system. Then comparison is made between FMGS approach and other options. Finally, the technology developmental needs are identified.

Ramakumar, R.; Bahrami, K.

1979-08-15T23:59:59.000Z

47

The ANEMOS Project: Next Generation Forecasting of Wind Power. G.Kariniotakis*  

E-Print Network (OSTI)

integration of wind energy in the developing liberalized electricity markets. Keywords - Wind power, short-resolution meteorological forecasts. For the offshore case, marine meteorology is considered as well as information will allow validation of the models and an analysis of the value of wind prediction for a competitive

Heinemann, Detlev

48

Coherent infared radiation from the ALS generated via femtosecond laser modulation of the electron beam  

E-Print Network (OSTI)

INFRARED RADIATION FROM THE ALS GENERATED VIA FEMTOSECONDthrough a wiggler at the ALS produces large modulation oflocations for a nominal ALS lattice and for an experimental

2004-01-01T23:59:59.000Z

49

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

4 4 The commercial module forecasts consumption by fuel 15 at the Census division level using prices from the NEMS energy supply modules, and macroeconomic variables from the NEMS Macroeconomic Activity Module (MAM), as well as external data sources (technology characterizations, for example). Energy demands are forecast for ten end-use services 16 for eleven building categories 17 in each of the nine Census divisions (see Figure 5). The model begins by developing forecasts of floorspace for the 99 building category and Census division combinations. Next, the ten end-use service demands required for the projected floorspace are developed. The electricity generation and water and space heating supplied by distributed generation and combined heat and power technologies are projected. Technologies are then

50

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

DOE Green Energy (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

51

Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation  

Science Conference Proceedings (OSTI)

Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-08-13T23:59:59.000Z

52

The effects of energy storage properties and forecast accuracy on mitigating variability in wind power generation  

E-Print Network (OSTI)

Electricity generation from wind power is increasing worldwide. Wind power can offset traditional fossil fuel generators which is beneficial to the environment. However, wind generation is unpredictable. Wind speeds have ...

Jaworsky, Christina A

2013-01-01T23:59:59.000Z

53

Commercial Sector Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Kevin Jarzomski

2012-11-15T23:59:59.000Z

54

Commercial Sector Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Kevin Jarzomski

2013-10-10T23:59:59.000Z

55

Forecast Correlation Coefficient Matrix of Stock Returns in Portfolio Analysis  

E-Print Network (OSTI)

Unadjusted Forecasts . . . . . . . . . . . . . . . .Forecasts . . . . . . . . . . . . . . . . . . . . . . . . . .Unadjusted Forecasts . . . . . . . . . . . . . . . . . . .

Zhao, Feng

2013-01-01T23:59:59.000Z

56

Phase matching of high order harmonic generation using dynamic phase modulation caused by a non-collinear modulation pulse  

DOE Patents (OSTI)

Phase matching high harmonic generation (HHG) uses a single, long duration non-collinear modulating pulse intersecting the driving pulse. A femtosecond driving pulse is focused into an HHG medium (such as a noble gas) to cause high-harmonic generation (HHG), for example in the X-ray region of the spectrum, via electrons separating from and recombining with gas atoms. A non-collinear pulse intersects the driving pulse within the gas, and modulates the field seen by the electrons while separated from their atoms. The modulating pulse is low power and long duration, and its frequency and amplitude is chosen to improve HHG phase matching by increasing the areas of constructive interference between the driving pulse and the HHG, relative to the areas of destructive interference.

Cohen, Oren (Boulder, CO); Kapteyn, Henry C. (Boulder, CO); Mumane, Margaret M. (Boulder, CO)

2010-02-16T23:59:59.000Z

57

Forecast Technical Document Forecast Types  

E-Print Network (OSTI)

Forecast Technical Document Forecast Types A document describing how different forecast types are implemented in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Forecast Types Background Different `types' of forecast are possible for a specified area

58

Method and device for generating microwaves using a split cavity modulator  

DOE Patents (OSTI)

This invention consists of a compact device called the split cavity modulator whose self-generated oscillating electromagnetic field converts a steady particle beam into a modulated particle beam. The particle beam experiences both signs of the oscillating electric field during the transit through the split cavity modulator. The modulated particle beam can then be used to generate microwaves as that frequency and through a series of sequential extractors, high efficiency extraction of microwave power is enabled. The modulated beam and the microwave frequency can be varied by the placement of resistive wires at nodes of oscillation within the cavity. The short beam travel length through the cavity permit higher currents because both space charge and pinching limitations are reduced. The need for an applied magnetic field to control the beam has been eliminated.

Clark, M.C.; Coleman, P.D.; Marder, B.M.

1990-01-01T23:59:59.000Z

59

Method and split cavity oscillator/modulator to generate pulsed particle beams and electromagnetic fields  

DOE Patents (OSTI)

A compact device called the split cavity modulator whose self-generated oscillating electromagnetic field converts a steady particle beam into a modulated particle beam. The particle beam experiences both signs of the oscillating electric field during the transit through the split cavity modulator. The modulated particle beam can then be used to generate microwaves at that frequency and through the use of extractors, high efficiency extraction of microwave power is enabled. The modulated beam and the microwave frequency can be varied by the placement of resistive wires at nodes of oscillation within the cavity. The short beam travel length through the cavity permit higher currents because both space charge and pinching limitations are reduced. The need for an applied magnetic field to control the beam has been eliminated.

Clark, M.C.; Coleman, P.D.; Marder, B.M.

1993-08-10T23:59:59.000Z

60

Method and device for generating microwaves using a split cavity modulator  

DOE Patents (OSTI)

This invention consists of a compact device called the split cavity modulator whose self-generated oscillating electromagnetic field converts a steady particle beam into a modulated particle beam. The particle beam experiences both signs of the oscillating electric field during the transit through the split cavity modulator. The modulated particle beam can then be used to generate microwaves as that frequency and through a series of sequential extractors, high efficiency extraction of microwave power is enabled. The modulated beam and the microwave frequency can be varied by the placement of resistive wires at nodes of oscillation within the cavity. The short beam travel length through the cavity permit higher currents because both space charge and pinching limitations are reduced. The need for an applied magnetic field to control the beam has been eliminated.

Clark, M.C.; Coleman, P.D.; Marder, B.M.

1990-12-31T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Method and split cavity oscillator/modulator to generate pulsed particle beams and electromagnetic fields  

DOE Patents (OSTI)

A compact device called the split cavity modulator whose self-generated oscillating electromagnetic field converts a steady particle beam into a modulated particle beam. The particle beam experiences both signs of the oscillating electric field during the transit through the split cavity modulator. The modulated particle beam can then be used to generate microwaves at that frequency and through the use of extractors, high efficiency extraction of microwave power is enabled. The modulated beam and the microwave frequency can be varied by the placement of resistive wires at nodes of oscillation within the cavity. The short beam travel length through the cavity permit higher currents because both space charge and pinching limitations are reduced. The need for an applied magnetic field to control the beam has been eliminated.

Clark, M. Collins (Albuquerque, NM); Coleman, P. Dale (Albuquerque, NM); Marder, Barry M. (Albuquerque, NM)

1993-01-01T23:59:59.000Z

62

Operational Forecasting of Wind-Generated Waves by Hurricane Isabel at NCEP  

Science Conference Proceedings (OSTI)

The accuracy of the operational wave models at the National Centers for Environmental Prediction (NCEP) for sea states generated by Hurricane Isabel is assessed. The western North Atlantic (WNA) and the North Atlantic hurricane (NAH) wave models ...

Hendrik L. Tolman; Jose-Henrique G. M. Alves; Yung Y. Chao

2005-08-01T23:59:59.000Z

63

Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation  

DOE Green Energy (OSTI)

Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-08-13T23:59:59.000Z

64

California Regional Wind Energy Forecasting System Development, Volume 4: California Wind Generation Research Dataset (CARD)  

Science Conference Proceedings (OSTI)

The rated capacity of wind generation in California is expected to grow rapidly in the future beyond the approximately 2100 megawatts in place at the end of 2005. The main drivers are the state's 20 percent renewable portfolio standard requirement in 2010 and the low cost of wind energy relative to other renewable energy sources. As wind is an intermittent generation resource and weather changes can cause large and rapid changes in output, system operators will need accurate and robust wind energy forec...

2006-11-13T23:59:59.000Z

65

Single module pressurized fuel cell turbine generator system  

DOE Patents (OSTI)

A pressurized fuel cell system (10), operates within a common pressure vessel (12) where the system contains fuel cells (22), a turbine (26) and a generator (98) where preferably, associated oxidant inlet valve (52), fuel inlet valve (56) and fuel cell exhaust valve (42) are outside the pressure vessel.

George, Raymond A. (Pittsburgh, PA); Veyo, Stephen E. (Murrysville, PA); Dederer, Jeffrey T. (Valencia, PA)

2001-01-01T23:59:59.000Z

66

Similarity retrieval from time-series tropical cyclone observations using a neural weighting generator for forecasting modeling  

Science Conference Proceedings (OSTI)

Building a forecasting model for time-series data is a tough but very valuable research topic in recent years. High variation of time-series features must be considered appropriately for an accurate prediction. For weather forecasting, which is continuous, ...

Bo Feng; James N. K. Liu

2005-09-01T23:59:59.000Z

67

RACORO Forecasting  

NLE Websites -- All DOE Office Websites (Extended Search)

Weather Briefings Observed Weather Cloud forecasting models BUFKIT forecast soundings + guidance from Norman NWS enhanced pages and discussions NAM-WRF updated...

68

Evaluation of Wave Forecasts Consistent with Tropical Cyclone Warning Center Wind Forecasts  

Science Conference Proceedings (OSTI)

An algorithm to generate wave fields consistent with forecasts from the official U.S. tropical cyclone forecast centers has been made available in near–real time to forecasters since summer 2007. The algorithm removes the tropical cyclone from ...

Charles R. Sampson; Paul A. Wittmann; Efren A. Serra; Hendrik L. Tolman; Jessica Schauer; Timothy Marchok

2013-02-01T23:59:59.000Z

69

Estimating Water Needs to Meet 2025 Electricity Generating Capacity Forecasts by NERC Region  

NLE Websites -- All DOE Office Websites (Extended Search)

NETL-2006/1235 NETL-2006/1235 August 2006 Revised April 8, 2008 Estimating Freshwater Needs to Meet Future Thermoelectric Generation Requirements Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement,

70

Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1994--FY 2001. Environmental Restoration Program, September 1993 Revision  

Science Conference Proceedings (OSTI)

This Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project. FY 1994--FY 2001 is the third in a series of documents that report current estimates of the waste volumes expected to be generated as a result of Environmental Restoration activities at Department of Energy, Oak Ridge Operations Office (DOE-ORO), sites. Considered in the scope of this document are volumes of waste expected to be generated as a result of remedial action and decontamination and decommissioning activities taking place at these sites. Sites contributing to the total estimates make up the DOE-ORO Environmental Restoration OR-1 Project: the Oak Ridge K-25 Site, the Oak Ridge National Laboratory, the Y-12 Plant, the Paducah Gaseous Diffusion Plant, the Portsmouth Gaseous Diffusion Plant, and the off-site contaminated areas adjacent to the Oak Ridge facilities (collectively referred to as the Oak Ridge Reservation Off-Site area). Estimates are available for the entire fife of all waste generating activities. This document summarizes waste estimates forecasted for the 8-year period of FY 1994-FY 2001. Updates with varying degrees of change are expected throughout the refinement of restoration strategies currently in progress at each of the sites. Waste forecast data are relatively fluid, and this document represents remediation plans only as reported through September 1993.

Not Available

1993-12-01T23:59:59.000Z

71

Quasi-Biweekly Mode and Its Modulation on the Diurnal Rainfall in Taiwan Forecasted by the CFS  

Science Conference Proceedings (OSTI)

The occurrence of diurnal afternoon convection in Taiwan undergoes substantial modulation from tropical intraseasonal oscillations in the western North Pacific, including the quasi-biweekly (QBW) mode. By analyzing surface station observations and ...

Shih-Yu Wang; Hsin-Hsing Chia; Robert R. Gillies; Xianan Jiang

2013-08-01T23:59:59.000Z

72

Forecasting Forecast Skill  

Science Conference Proceedings (OSTI)

We have shown that it is possible to predict the skill of numerical weather forecasts—a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average ...

Eugenia Kalnay; Amnon Dalcher

1987-02-01T23:59:59.000Z

73

UWIG Forecasting Workshop -- Albany (Presentation)  

SciTech Connect

This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

Lew, D.

2011-04-01T23:59:59.000Z

74

Forecast Combinations  

E-Print Network (OSTI)

Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this chapter we analyze theoretically the factors that determine the advantages from combining forecasts (for example, the degree of correlation between forecast errors and the relative size of the individual models’ forecast error variances). Although the reasons for the success of simple combination schemes are poorly understood, we discuss several possibilities related to model misspecification, instability (non-stationarities) and estimation error in situations where thenumbersofmodelsislargerelativetothe available sample size. We discuss the role of combinations under asymmetric loss and consider combinations of point, interval and probability forecasts. Key words: Forecast combinations; pooling and trimming; shrinkage methods; model misspecification, diversification gains

Allan Timmermann; Jel Codes C

2006-01-01T23:59:59.000Z

75

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

the entire forecast period, primarily because both weather-adjusted peak and electricity consumption were forecast. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, conservation, California Solar Initiative. #12

76

Precipitation and Temperature Forecast Performance at the Weather Prediction Center  

Science Conference Proceedings (OSTI)

The role of the human forecaster in improving upon the accuracy of numerical weather prediction is explored using multi-year verification of human-generated short-range precipitation forecasts and medium-range maximum temperature forecasts from ...

David R. Novak; Christopher Bailey; Keith Brill; Patrick Burke; Wallace Hogsett; Robert Rausch; Michael Schichtel

77

Rolling 12 Month Forecast November-2008.xls  

NLE Websites -- All DOE Office Websites (Extended Search)

Month Exceedence Level: 90% (Dry) First Preference CVP Generation Project Use November 2008 October 2009 November 2008 Twelve-Month Forecast of CVP Generation and Base Resource...

78

Probabilistic Visibility Forecasting Using Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Bayesian model averaging (BMA) is a statistical postprocessing technique that has been used in probabilistic weather forecasting to calibrate forecast ensembles and generate predictive probability density functions (PDFs) for weather quantities. ...

Richard M. Chmielecki; Adrian E. Raftery

2011-05-01T23:59:59.000Z

79

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.

80

Post-test analysis of components from selenide isotope generator modules M-7, M-15, and M-18  

DOE Green Energy (OSTI)

Several critical components removed from SIG (Selenide Isotope Generator) thermoelectric modules M-7, M-15C, M-15D, and M-18 were examined. These modules failed to show the predicted stability and conversion efficiency. Understanding the degradation and identifying means for preventing it necessitated detailed post-test examinations of key parts in the modules. Steel springs, which provided pressure for contacts at the hot and cold ends of P- or N-legs, relaxed more than expected. Beryllium oxide insulators had dark deposits that caused electrical shorts. The GdSe/sub 1/ /sub 49/ N-leg exhibited cracking. The (Cu,Ag)/sub 2/Se P-leg lost weight or sublimed excessively in module M-7 and more than expected in the other modules.

Wei, G.C.; Keiser, J.R.; Crouse, R.S.; Allen, M.D.; Schaffhauser, A.C.

1979-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Solar forecasting review  

E-Print Network (OSTI)

of Solar Forecasting . . . . . . . . . 2.4.1 Solarbudget at the foundation of satellite based forecastingWeather Research and Forecasting (WRF) Model 7.1 Global

Inman, Richard Headen

2012-01-01T23:59:59.000Z

82

NFI Forecasts Methodology NFI Forecasts Methodology  

E-Print Network (OSTI)

NFI Forecasts Methodology NFI Forecasts Methodology Overview Issued by: National Forest Inventory.brewer@forestry.gsi.gov.uk Website: www.forestry.gov.uk/inventory 1 NFI Softwood Forecasts Methodology Overview #12;NFI Forecasts ........................................................................................................4 Rationale behind the new approach to the GB Private sector production forecast ........4 Volume

83

Forecast Technical Document Restocking in the Forecast  

E-Print Network (OSTI)

Forecast Technical Document Restocking in the Forecast A document describing how restocking of felled areas is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the forecast Background During the period of a production forecast it is assumed that, as forest sub

84

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS FORECAST IMPROVEMENTS  

E-Print Network (OSTI)

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS BRISBANE FORECAST IMPROVEMENTS The Bureau of Meteorology is progressively upgrading its forecast system to provide more detailed forecasts across Australia. From October 2013 new and improved 7 day forecasts will be introduced for Brisbane, Gold Coast

Greenslade, Diana

85

RESERVOIR INFLOW FORECASTING USING NEURAL NETWORKS CHANDRASHEKAR SUBRAMANIAN  

E-Print Network (OSTI)

or over predicting electricity demand due to poor weather forecasts is several hundred million dollars outages that many in the area experienced. Deep Thunder can also improve generation-side load forecasting by providing high-resolution weather forecast data for use in electricity demand forecast models. Integrating

Manry, Michael

86

Model documentation: Electricity Market Module, Electricity Fuel Dispatch Submodule  

SciTech Connect

This report documents the objectives, analytical approach and development of the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Not Available

1994-04-08T23:59:59.000Z

87

Another Approach to Forecasting Forecast Skill  

Science Conference Proceedings (OSTI)

The skill of a medium-range numerical forecast can fluctuate widely from day to day. Providing an a priori estimate of the skill of the forecast is therefore important. Existing approaches include Monte Carlo Forecasting and Lagged Average ...

W. Y. Chen

1989-02-01T23:59:59.000Z

88

New generation polyphase resonant converter-modulators for the Korean atomic energy research institute  

SciTech Connect

This paper will present operational data and performance parameters of the newest generation polyphase resonant high voltage converter modulator (HVCM) as developed and delivered to the KAERI 100 MeV ''PEFP'' accelerator [1]. The KAERI design realizes improvements from the SNS and SLAC designs [2]. To improve the IGBT switching performance at 20 kHz for the KAERI system, the HVCM utilizes the typical zero-voltage-switching (ZVS) at turn on and as well as artificial zero-current-switching (ZCS) at turn-off. The new technique of artificial ZCS technique should result in a 6 fold reduction of IGBT switching losses (3). This improves the HCVM conversion efficiency to better than 95% at full average power, which is 500 kW for the KAERI two klystron 105 kV, 50 A application. The artificial ZCS is accomplished by placing a resonant RLC circuit across the input busswork to the resonant boost transformer. This secondary resonant circuit provides a damped ''kick-back'' to assist in IGBT commutation. As the transformer input busswork is extremely low inductance (< 10 nH), the single RLC network acts like it is across each of the four IGBT collector-emitter terminals of the H-bridge switching network. We will review these topological improvements and the overall system as delivered to the KAERI accelerator and provide details of the operational results.

Reass, William A [Los Alamos National Laboratory; Baca, David M [Los Alamos National Laboratory; Gribble, Robert F [Los Alamos National Laboratory

2009-01-01T23:59:59.000Z

89

Delays and cancellations of coal-fired generating capacity: review, data evaluation, and recommendations for improved forecasting  

Science Conference Proceedings (OSTI)

This report documents the extent of the electric utilities' difficulty in planning power generating units and proposes a technique for improving the predictions. Additional work is currently under way to test the methodology proposed here. The results of these efforts will be reported in a companion volume as soon as they are available. Chapter 1 examines delays and cancellations from a historical perspective. It evaluates the reasons for the difficulty and the potential impact on the electric utility industry and the electric power consumer. Chapter 2 examines the relationships between delays and cancellations, and identifies the data that could be used in an improved prediction method. Three methods are discussed, based on three types of data, and one system is recommended for implementation.

Not Available

1983-07-01T23:59:59.000Z

90

Bulk flows from galaxy luminosities: application to 2MASS redshift survey and forecast for next-generation datasets  

E-Print Network (OSTI)

We present a simple method for measuring cosmological bulk flows from large redshift surveys, based on the apparent dimming or brightening of galaxies due to their peculiar motion. It is aimed at estimating bulk flows of cosmological volumes containing large numbers of galaxies. Constraints on the bulk flow are obtained by minimizing systematic variations in galaxy luminosities with respect to a reference luminosity function measured from the whole survey. This method offers two advantages over more popular bulk flow estimators: it is independent of error-prone distance indicators and of the poorly-known galaxy bias. We apply the method to the 2MASS redshift survey (2MRS) to measure the local bulk flows of spherical shells centered on the Milky Way (MW). The result is consistent with that obtained by Nusser and Davis (2011) using the SFI++ catalogue of Tully-Fisher distance indicators. We also make an assessment of the ability of the method to constrain bulk flows at larger redshifts ($z=0.1-0.5$) from next generation datasets. As a case study we consider the planned EUCLID survey. Using this method we will be able to measure a bulk motion of $ \\sim 200 \\kms$ of $10^6$ galaxies with photometric redshifts, at the $3\\sigma$ level for both $z\\sim 0.15$ and $z\\sim 0.5$. Thus the method will allow us to put strong constraints on dark energy models as well as alternative theories for structure formation.

Adi Nusser; Enzo Branchini; Marc Davis

2011-02-21T23:59:59.000Z

91

Evaluation of Short-Range Quantitative Precipitation Forecasts from a Time-Lagged Multimodel Ensemble  

Science Conference Proceedings (OSTI)

Short-range quantitative precipitation forecasts (QPFs) and probabilistic QPFs (PQPFs) are investigated for a time-lagged multimodel ensemble forecast system. One of the advantages of such an ensemble forecast system is its low-cost generation of ...

Huiling Yuan; Chungu Lu; John A. McGinley; Paul J. Schultz; Brian D. Jamison; Linda Wharton; Christopher J. Anderson

2009-02-01T23:59:59.000Z

92

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

93

Western Area Power Administration Starting Forecast Month: Sierra...  

NLE Websites -- All DOE Office Websites (Extended Search)

Month CVP Generation Project Use First Preference Purchases and Exchanges Base Resource January 2014 Twelve-Month Forecast of CVP Generation and Base Resource January 2014 December...

94

ELECTRICITY DEMAND FORECAST COMPARISON REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 ..............................................................................3 Residential Forecast Comparison ..............................................................................................5 Nonresidential Forecast Comparisons

95

The Forecast Gap: Linking Forwards and Forecasts  

Science Conference Proceedings (OSTI)

This report addresses a common problem in price forecasting: What to do when confronted with a persistent gap between results obtained from a structural forecast model and actual forward or spot prices? The report examines examples taken from natural gas and electric power forecasts and presents a novel approach to closing this “forecast gap.” Inspection reveals that the ratio of actual prices to forecast prices often exhibits stochastic movements that resemble those of commodity price movements. By usin...

2008-12-15T23:59:59.000Z

96

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 23 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 International Energy Module The NEMS International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the NEMS IEM computes world oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into

97

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 International Energy Module The NEMS International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the NEMS IEM computes oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into the United States by export region. Changes in the oil price (WTI), which is defined as the price of light, low-sulfur crude oil delivered to Cushing, Oklahoma in

98

Real-Time Data Assimilation for Operational Ensemble Streamflow Forecasting  

Science Conference Proceedings (OSTI)

Operational flood forecasting requires that accurate estimates of the uncertainty associated with model-generated streamflow forecasts be provided along with the probable flow levels. This paper demonstrates a stochastic ensemble implementation ...

Jasper A. Vrugt; Hoshin V. Gupta; BreanndánÓ Nualláin; Willem Bouten

2006-06-01T23:59:59.000Z

99

Interpretation of Rank Histograms for Verifying Ensemble Forecasts  

Science Conference Proceedings (OSTI)

Rank histograms are a tool for evaluating ensemble forecasts. They are useful for determining the reliability of ensemble forecasts and for diagnosing errors in its mean and spread. Rank histograms are generated by repeatedly tallying the rank of ...

Thomas M. Hamill

2001-03-01T23:59:59.000Z

100

Emergency Response Transport Forecasting Using Historical Wind Field Pattern Matching  

Science Conference Proceedings (OSTI)

Historical pattern matching, or analog forecasting, is used to generate short-term mesoscale transport forecasts for emergency response at the Idaho National Engineering and Environmental Laboratory. A simple historical pattern-matching algorithm ...

Roger G. Carter; Robert E. Keislar

2000-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Evaluating the Cloud Cover Forecast of NCEP Global Forecast System with Satellite Observation  

E-Print Network (OSTI)

To assess the quality of daily cloud cover forecast generated by the operational global numeric model, the NCEP Global Forecast System (GFS), we compose a large sample with outputs from GFS model and satellite observations from the International Satellite Cloud Climatology Project (ISCCP) in the period of July 2004 to June 2008, to conduct a quantitative and systematic assessment of the performance of a cloud model that covers a relatively long range of time, basic cloud types, and in a global view. The evaluation has revealed the goodness of the model forecast, which further illustrates our completeness on understanding cloud generation mechanism. To quantity the result, we found a remarkably high correlation between the model forecasts and the satellite observations over the entire globe, with mean forecast error less than 15% in most areas. Considering a forecast within 30% difference to the observation to be a "good" one, we find that the probability for the GFS model to make good forecasts varies between...

Ye, Quanzhi

2011-01-01T23:59:59.000Z

102

Assumptions to the Annual Energy Outlook 2001 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2001, DOE/EIA-M060(2001) January 2001. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

103

Assumptions to the Annual Energy Outlook 2002 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2002, DOE/EIA-M060(2002) (Washington, DC, January 2002). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

104

A Review of Quantitative Precipitation Forecasts and Their Use in Short- to Medium-Range Streamflow Forecasting  

Science Conference Proceedings (OSTI)

Unknown future precipitation is the dominant source of uncertainty for many streamflow forecasts. Numerical weather prediction (NWP) models can be used to generate quantitative precipitation forecasts (QPF) to reduce this uncertainty. The ...

Lan Cuo; Thomas C. Pagano; Q. J. Wang

2011-10-01T23:59:59.000Z

105

Forecasting in Meteorology  

Science Conference Proceedings (OSTI)

Public weather forecasting heralded the beginning of modern meteorology less than 150 years ago. Since then, meteorology has been largely a forecasting discipline. Thus, forecasting could have easily been used to test and develop hypotheses, ...

C. S. Ramage

1993-10-01T23:59:59.000Z

106

Renewable Fuels Module  

Reports and Publications (EIA)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the Annual Energy Outlook forecasts.

Chris Namovicz

2013-07-03T23:59:59.000Z

107

Model documentation report: Residential sector demand module of the national energy modeling system  

SciTech Connect

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies, market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.

NONE

1998-01-01T23:59:59.000Z

108

Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1  

E-Print Network (OSTI)

Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts............................................................................................................................... 12 Oil Price Forecast Range

109

Load Forecasting Using Support Vector Machines: A Study on EUNITE  

E-Print Network (OSTI)

-Domain Market Information to Forecast Ontario's Wholesale Electricity Prices Hamidreza Zareipour, Student Member volatility analyses are presented. Index Terms--Electricity markets, price forecasting, time series models on-site generation facilities. Given such a wide variety of options, forecasting the electricity

Lin, Chih-Jen

110

A Buildings Module for the Stochastic Energy Deployment System  

SciTech Connect

The U.S. Department of Energy (USDOE) is building a new long-range (to 2050) forecasting model for use in budgetary and management applications called the Stochastic Energy Deployment System (SEDS), which explicitly incorporates uncertainty through its development within the Analytica(R) platform of Lumina Decision Systems. SEDS is designed to be a fast running (a few minutes), user-friendly model that analysts can readily run and modify in its entirety through a visual programming interface. Lawrence Berkeley National Laboratory is responsible for implementing the SEDS Buildings Module. The initial Lite version of the module is complete and integrated with a shared code library for modeling demand-side technology choice developed by the National Renewable Energy Laboratory (NREL) and Lumina. The module covers both commercial and residential buildings at the U.S. national level using an econometric forecast of floorspace requirement and a model of building stock turnover as the basis for forecasting overall demand for building services. Although the module is fundamentally an engineering-economic model with technology adoption decisions based on cost and energy performance characteristics of competing technologies, it differs from standard energy forecasting models by including considerations of passive building systems, interactions between technologies (such as internal heat gains), and on-site power generation.

Lacommare, Kristina S H; Marnay, Chris; Stadler, Michael; Borgeson, Sam; Coffey, Brian; Komiyama, Ryoichi; Lai, Judy

2008-05-15T23:59:59.000Z

111

Multi-standard programmable baseband modulator for next generation wireless communication  

E-Print Network (OSTI)

Considerable research has taken place in recent times in the area of parameterization of software defined radio (SDR) architecture. Parameterization decreases the size of the software to be downloaded and also limits the hardware reconfiguration time. The present paper is based on the design and development of a programmable baseband modulator that perform the QPSK modulation schemes and as well as its other three commonly used variants to satisfy the requirement of several established 2G and 3G wireless communication standards. The proposed design has been shown to be capable of operating at a maximum data rate of 77 Mbps on Xilinx Virtex 2-Pro University field programmable gate array (FPGA) board. The pulse shaping root raised cosine (RRC) filter has been implemented using distributed arithmetic (DA) technique in the present work in order to reduce the computational complexity, and to achieve appropriate power reduction and enhanced throughput. The designed multiplier-less programmable 32-tap FIR-based RRC ...

Hatai, Indranil; 10.5121/ijcnc.2010.2406

2010-01-01T23:59:59.000Z

112

Generator module architecture for a large solid oxide fuel cell power plant  

DOE Patents (OSTI)

A solid oxide fuel cell module contains a plurality of integral bundle assemblies, the module containing a top portion with an inlet fuel plenum and a bottom portion receiving air inlet feed and containing a base support, the base supports dense, ceramic exhaust manifolds which are below and connect to air feed tubes located in a recuperator zone, the air feed tubes passing into the center of inverted, tubular, elongated, hollow electrically connected solid oxide fuel cells having an open end above a combustion zone into which the air feed tubes pass and a closed end near the inlet fuel plenum, where the fuel cells comprise a fuel cell stack bundle all surrounded within an outer module enclosure having top power leads to provide electrical output from the stack bundle, where the fuel cells operate in the fuel cell mode and where the base support and bottom ceramic air exhaust manifolds carry from 85% to all 100% of the weight of the stack, and each bundle assembly has its own control for vertical and horizontal thermal expansion control.

Gillett, James E.; Zafred, Paolo R.; Riggle, Matthew W.; Litzinger, Kevin P.

2013-06-11T23:59:59.000Z

113

Application of the NCEP Ensemble Prediction System to Medium-Range Forecasting in South Africa: New Products, Benefits, and Challenges  

Science Conference Proceedings (OSTI)

The National Centers for Environmental Prediction (NCEP) Ensemble Forecasting System (EFS) is used operationally in South Africa for medium-range forecasts up to 14 days ahead. The use of model-generated probability forecasts has a clear benefit ...

Warren J. Tennant; Zoltan Toth; Kevin J. Rae

2007-02-01T23:59:59.000Z

114

NCEP Dynamical Seasonal Forecast System 2000  

Science Conference Proceedings (OSTI)

The new National Centers for Environmental Prediction (NCEP) numerical seasonal forecast system is described in detail. The new system is aimed at a next-generation numerical seasonal prediction in which focus is placed on land processes, initial ...

Masao Kanamitsu; Arun Kumar; Hann-Ming Henry Juang; Jae-Kyung Schemm; Wanqui Wang; Fanglin Yang; Song-You Hong; Peitao Peng; Wilber Chen; Shrinivas Moorthi; Ming Ji

2002-07-01T23:59:59.000Z

115

MM5 Contrail Forecasting in Alaska  

Science Conference Proceedings (OSTI)

The fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) is being used for forecasting the atmospheric layers of aircraft condensation trail (contrail) formation. Contrail ...

Martin Stuefer; Xiande Meng; Gerd Wendler

2005-12-01T23:59:59.000Z

116

Generation of ELF and VLF waves by HF-modulated polar electrojet via a thermal instability process  

SciTech Connect

Generation of ELF and VLF waves via a thermal instability process in a HF-modulated polar electrojet has been investigated. It is shown that a positive feedback through the electron-neutral collisional heating process can cause the transient response of the plasma to the modulated HF heater to grow exponentially. The threshold fields of the instability under normal electrojet conditions are found to be about 2.25 V/m and 1.13 V/m for the operation of the o-mode and x-mode heaters with a 50% duty cycle, respectively. For a heater wave field of, e.g., 1.5 V/m, the instability can be excited by the x-mode heater within a few tens of millisecond. The predicted dependence of the ELF/VLF radiation amplitude on the percentage of the duty cycle of the HF modulation is identical to that of the recent observational results of Barr and Stubbe. 28 refs., 2 figs.

Kuo, S.P. (Polytechnic Univ., Farmingdale, NY (United States)); Lee, M.C. (Massachusetts Inst. of Technology, Cambridge (United States))

1993-02-05T23:59:59.000Z

117

Forecasts, Meteorology Services, Environmental Sciences Department  

NLE Websites -- All DOE Office Websites (Extended Search)

Forecasts Short Term Forecast Suffolk County Northern Nassau Southern Nassau Area Forecast Discussion - OKX Area Forecast Discussion - NYS Area Forecast Discussion Mount Holly Area...

118

1993 Solid Waste Reference Forecast Summary  

SciTech Connect

This report, which updates WHC-EP-0567, 1992 Solid Waste Reference Forecast Summary, (WHC 1992) forecasts the volumes of solid wastes to be generated or received at the US Department of Energy Hanford Site during the 30-year period from FY 1993 through FY 2022. The data used in this document were collected from Westinghouse Hanford Company forecasts as well as from surveys of waste generators at other US Department of Energy sites who are now shipping or plan to ship solid wastes to the Hanford Site for disposal. These wastes include low-level and low-level mixed waste, transuranic and transuranic mixed waste, and nonradioactive hazardous waste.

Valero, O.J.; Blackburn, C.L. [Westinghouse Hanford Co., Richland, WA (United States); Kaae, P.S.; Armacost, L.L.; Garrett, S.M.K. [Pacific Northwest Lab., Richland, WA (United States)

1993-08-01T23:59:59.000Z

119

Wind Energy Forecasting Technology Update: 2004  

Science Conference Proceedings (OSTI)

This report describes the status of wind energy forecasting technology for predicting wind speed and energy generation of wind energy facilities short-term (minutes to hours), intermediate-term (hours to days), and long-term (months to years) average wind speed and energy generation. The information should be useful to companies that are evaluating or planning to incorporate wind energy forecasting into their operations.

2005-04-26T23:59:59.000Z

120

Computational mass transfer moduling of flow through a photocatalytic oxygen generator  

E-Print Network (OSTI)

A self-contained, portable oxygen generator would be extraordinarily useful across a broad spectrum of industries. Both safety and energy-efficiency could be enhanced tremendously in fields such as coal mining, commercial ...

Köksal, Erin (Erin Sevim)

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Consistent Tropical Cyclone Wind and Wave Forecasts for the U.S. Navy  

Science Conference Proceedings (OSTI)

A new algorithm to generate wave heights consistent with tropical cyclone official forecasts from the Joint Typhoon Warning Center (JTWC) has been developed. The process involves generating synthetic observations from the forecast track and the ...

Charles R. Sampson; Paul A. Wittmann; Hendrik L. Tolman

2010-08-01T23:59:59.000Z

122

Western Area Power Administration Starting Forecast Month: Sierra...  

NLE Websites -- All DOE Office Websites (Extended Search)

Starting Forecast Month: Sierra Nevada Region Through Values at Load Center (Tracy Substation) Reg & Res CVP Maximum Capability CVP Energy Generation Peak Project Use Demand...

123

Western Area Power Administration Starting Forecast Month: Sierra...  

NLE Websites -- All DOE Office Websites (Extended Search)

based on Green Book ("Average") values. Base Resource September 2013 Twelve-Month Forecast of CVP Generation and Base Resource September 2013 August 2014 Exceedence Level: 90%...

124

Western Area Power Administration Starting Forecast Month: Sierra...  

NLE Websites -- All DOE Office Websites (Extended Search)

Use First Preference Purchases and Exchanges Base Resource October 2013 Twelve-Month Forecast of CVP Generation and Base Resource October 2013 September 2014 Exceedence Level: 90%...

125

Western Area Power Administration Starting Forecast Month: Sierra...  

NLE Websites -- All DOE Office Websites (Extended Search)

the 10% Exceedence Level based on Green Book ("Above Normal") values. Base Resource December 2013 Twelve-Month Forecast of CVP Generation and Base Resource December 2013 November...

126

Western Area Power Administration Starting Forecast Month: Sierra...  

NLE Websites -- All DOE Office Websites (Extended Search)

Use First Preference Purchases and Exchanges Base Resource April 2013 Twelve-Month Forecast of CVP Generation and Base Resource April 2013 March 2014 Exceedence Level: 90% (Dry)...

127

Managing Wind Power Forecast Uncertainty in Electric Grids.  

E-Print Network (OSTI)

??Electricity generated from wind power is both variable and uncertain. Wind forecasts provide valuable information for wind farm management, but they are not perfect. Chapter… (more)

Mauch, Brandon Keith

2012-01-01T23:59:59.000Z

128

Verifying Forecasts Spatially  

Science Conference Proceedings (OSTI)

Numerous new methods have been proposed for using spatial information to better quantify and diagnose forecast performance when forecasts and observations are both available on the same grid. The majority of the new spatial verification methods can be ...

Eric Gilleland; David A. Ahijevych; Barbara G. Brown; Elizabeth E. Ebert

2010-10-01T23:59:59.000Z

129

Forecasting of Supercooled Clouds  

Science Conference Proceedings (OSTI)

Using parameterizations of cloud microphysics, a technique to forecast supercooled cloud events is suggested. This technique can be coupled on the mesoscale with a prognostic equation for cloud water to improve aircraft icing forecasts. The ...

André Tremblay; Anna Glazer; Wanda Szyrmer; George Isaac; Isztar Zawadzki

1995-07-01T23:59:59.000Z

130

FPGA Based Sinusoidal Pulse Width Modulated Waveform Generation for Solar (PV) Rural Home Power Inverter  

E-Print Network (OSTI)

With the increasing concern about global environmental protection and energy demand due to rapid growth of population in developing countries and the diminishing trend of resources of conventional grid supply, the need to produce freely available pollution free natural energy such as solar/wind energy has been drawing increasing interest in every corner of the world. In an effort to utilize these energies effectively through Power converter, a great deal of research is being carried out by different researchers / scientist and engineers at different places in the world to meet the increasing demand of load. The study presents methodology to integrate solar (PV) energy (which is freely available in every corner of the world) with grid source and supplement the existing grid power in rural houses during its cut off or restricted supply period. In order to get consistency in supply a DG is also added as a standby source in the proposed integration of network. The software using novel Direct PWM modulation strate...

Singh, S N

2010-01-01T23:59:59.000Z

131

Time Series and Forecasting  

Science Conference Proceedings (OSTI)

Time Series and Forecasting. Leigh, Stefan and Perlman, S. (1991). "An Index for Comovement of Time Sequences With ...

132

Forecast Technical Document Volume Increment  

E-Print Network (OSTI)

Forecast Technical Document Volume Increment Forecasts A document describing how volume increment is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Volume increment forecasts Background A volume increment forecast is a fundamental output of the forecast

133

Wind and Load Forecast Error Model for Multiple Geographically Distributed Forecasts  

Science Conference Proceedings (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

134

Wind Energy Forecasting Technology Update: 2006  

Science Conference Proceedings (OSTI)

The worldwide installed wind generation capacity increased by 25 and reached almost 60,000 MW worldwide during 2005. As wind capacity continues to grow and large regional concentrations of wind generation emerge, utilities and regional transmission organizations will increasingly need accurate same-day and next-day forecasts of wind energy generation to dispatch system generation and transmission resource and anticipate rapid changes of wind generation.

2006-12-05T23:59:59.000Z

135

Wind Energy Forecasting Technology Update: 2005  

Science Conference Proceedings (OSTI)

The worldwide installed wind generation capacity increased by 25 and reached almost 60,000 MW worldwide during 2005. As wind capacity continues to grow and large regional concentrations of wind generation emerge, utilities and regional transmission organizations will increasingly need accurate same-day and next-day forecasts of wind energy generation to dispatch system generation and transmission resource and anticipate rapid changes of wind generation. The project objective is to summarize the results o...

2006-03-31T23:59:59.000Z

136

The Strategy of Professional Forecasting  

E-Print Network (OSTI)

This paper develops and compares two theories of strategic behavior of professional forecasters. The first theory posits that forecasters compete in a forecasting contest with pre-specified rules. In equilibrium of a winner-take-all contest, forecasts are excessively differentiated. According to the alternative reputational cheap talk theory, forecasters aim at convincing the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts and the realized state. If the market expects forecaster honesty, forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded.

Marco Ottaviani; Peter Norman Sřrensen

2003-01-01T23:59:59.000Z

137

Assumptions to the Annual Energy Outlook 2000 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

138

Microsoft PowerPoint - FinalModule6.ppt  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

6: Metrics, Performance 6: Metrics, Performance Measurements and Forecasting Prepared by: Module 6 - Metrics, Performance Measures and Forecasting 2 Prepared by: Booz Allen Hamilton Module 6: Metrics, Performance Measurements and Forecasting Welcome to Module 6. The objective of this module is to introduce you to the Metrics and Performance Measurement tools used, along with Forecasting, in Earned Value Management. The Topics that will be addressed in this Module include: * Define Cost and Schedule Variances * Define Cost and Schedule Performance Indices * Define Estimate to Complete (ETC) * Define Estimate at Completion (EAC) and Latest Revised Estimate (LRE) Module 6 - Metrics, Performance Measures and Forecasting 3 Prepared by: Booz Allen Hamilton Review of Previous Modules Let's quickly review what has been covered in the previous modules.

139

Business forecasting methods  

E-Print Network (OSTI)

Forecasting is a common statistical task in business, where it helps inform decisions about scheduling of production, transportation and personnel, and provides a guide to long-term strategic planning. However, business forecasting is often done poorly and is frequently confused with planning and goals. They are three different things. Forecasting is about predicting the future as accurately as possible, given all the information available including historical data and knowledge of any future events that might impact the forecasts. Goals are what you would like to happen. Goals should be linked to forecasts and plans, but this does not always occur. Too often, goals are set without any plan for how to achieve them, and no forecasts for whether they are realistic. Planning is a response to forecasts and goals. Planning involves determining the appropriate actions that are required to make your forecasts match your goals. Forecasting should be an integral part of the decision-making activities of management, as it can play an important role in many areas of a company. Modern organizations require short-, medium- and long-term forecasts, depending on the specific application.

Rob J Hyndman

2009-01-01T23:59:59.000Z

140

Assumptions to the Annual Energy Outlook 1999 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

coal.gif (4423 bytes) coal.gif (4423 bytes) The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Model Documentation: Coal Market Module of the National Energy Modeling System, DOE/EIA-MO60. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

Note: This page contains sample records for the topic "module generates forecasts" 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

Realizations of Daily Weather in Forecast Seasonal Climate  

Science Conference Proceedings (OSTI)

Stochastic daily weather time series models (?“weather generators”?) are parameterized consistent with both local climate and probabilistic seasonal forecasts. Both single-station weather generators, and spatial networks of coherently operating ...

D. S. Wilks

2002-04-01T23:59:59.000Z

142

ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL  

E-Print Network (OSTI)

5.5 ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL USING RETROSPECTIVE FORECASTS, Colorado 1. INTRODUCTION Improving weather forecasts is a primary goal of the U.S. National Oceanic predictions has been to improve the accuracy of the numerical forecast models. Much effort has been expended

Hamill, Tom

143

Transportation Sector Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2012-10-31T23:59:59.000Z

144

Transportation Sector Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2013-09-05T23:59:59.000Z

145

Evaluation of a Wind-Wave System for Ensemble Tropical Cyclone Wave Forecasting. Part II: Waves  

Science Conference Proceedings (OSTI)

A wind-wave forecast system, designed with the intention of generating unbiased ensemble wave forecasts for extreme wind events, is assessed. Wave hindcasts for 12 tropical cyclones (TCs) are forced using a wind analysis produced from a ...

Steven M. Lazarus; Samuel T. Wilson; Michael E. Splitt; Gary A. Zarillo

2013-04-01T23:59:59.000Z

146

Status of Centralized Wind Power Forecasting in North America: May 2009-May 2010  

SciTech Connect

Report surveys grid wind power forecasts for all wind generators, which are administered by utilities or regional transmission organizations (RTOs), typically with the assistance of one or more wind power forecasting companies.

Porter, K.; Rogers, J.

2010-04-01T23:59:59.000Z

147

Improving Probabilistic Ensemble Forecasts of Convection through the Application of QPF–POP Relationships  

Science Conference Proceedings (OSTI)

Four new approaches of postprocessing quantitative precipitation forecasts (QPFs) from model ensemble output were used to generate probability of precipitation (POP) tables in order to develop a forecasting method that could outperform a ...

Christopher J. Schaffer; William A. Gallus Jr.; Moti Segal

2011-06-01T23:59:59.000Z

148

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

149

STORMTIPE: A Forecasting Experiment Using a Three-Dimensional Cloud Model  

Science Conference Proceedings (OSTI)

An experiment using a three-dimensional cloud-scale numerical model in an operational forecasting environment was carried out in the spring of 1991. It involved meteorologists generating forecast environmental conditions associated with ...

Harold E. Brooks; Charles A. Doswell III; Louis J. Wicker

1993-09-01T23:59:59.000Z

150

Verification of Cloud Forecasts over the Eastern Pacific Using Passive Satellite Retrievals  

Science Conference Proceedings (OSTI)

Operational cloud forecasts generated by the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) were verified over the eastern Pacific Ocean. The study focused on the accuracy of cloud forecasts associated with extratropical cyclone ...

Jason E. Nachamkin; Jerome Schmidt; Cristian Mitrescu

2009-10-01T23:59:59.000Z

151

Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System  

DOE Green Energy (OSTI)

Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and direction, using its wind tunnel facility at the windmill farm at the Altamont Pass. The main objective of LLNL's involvement is to provide UC-Davis with improved wind forecasts to drive the parameterization scheme of turbine power curves developed from the wind tunnel facility. Another objective of LLNL's effort is to support the windmill farm operation with real-time wind forecasts for the effective energy management. The forecast skill in capturing the situation to meet the cut-in and cutout speed of given turbines would help reduce the operation cost in low and strong wind scenarios, respectively. The main focus of this report is to evaluate the wind forecast errors of LLNL's three-dimensional real-time weather forecast model at the location with the complex terrain. The assessment of weather forecast accuracy would help quantify the source of wind energy forecast errors from the atmospheric forecast model and/or wind-tunnel module for further improvement in the wind energy forecasting system.

Chin, H S

2005-07-26T23:59:59.000Z

152

ORNL integrated forecasting system  

SciTech Connect

This paper describes the integrated system for forecasting electric energy and load. In the system, service area models of electrical energy (kWh) and load distribution (minimum and maximum loads and load duration curve) are linked to a state-level model of electrical energy (kWh). Thus, the service area forecasts are conditional upon the state-level forecasts. Such a linkage reduces considerably the data requirements for modeling service area electricity demand.

Rizy, C.G.

1983-01-01T23:59:59.000Z

153

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 operation in terms of the efficiency of the system. The goal of this dissertation is to develop advanced statistical wind speed predictive models to reduce the uncertainties in wind, especially the short-term future wind speed. Moreover, a criterion is proposed to evaluate the performance of models. Cost reduction in power system operation, as proposed, is more realistic than prevalent criteria, such as, root mean square error (RMSE) and absolute mean error (MAE). Two advanced space-time statistical models are introduced for short-term wind speed forecasting. One is a modified regime-switching, space-time wind speed fore- casting model, which allows the forecast regimes to vary according to the dominant wind direction and seasons. Thus, it avoids a subjective choice of regimes. The other one is a novel model that incorporates a new variable, geostrophic wind, which has strong influence on the surface wind, into one of the advanced space-time statistical forecasting models. This model is motivated by the lack of improvement in forecast accuracy when using air pressure and temperature directly. Using geostrophic wind in the model is not only critical, it also has a meaningful geophysical interpretation. The importance of model evaluation is emphasized in the dissertation as well. Rather than using RMSE or MAE, the performance of both wind forecasting models mentioned above are assessed by economic benefits with real wind farm data from Pacific Northwest of the U.S and West Texas. Wind forecasts are incorporated into power system economic dispatch models, and the power system operation cost is used as a loss measure for the performance of the forecasting models. From another perspective, the new criterion leads to cost-effective scheduling of system-wide wind generation with potential economic benefits arising from the system-wide generation of cost savings and ancillary services cost savings. As an illustration, the integrated forecasts and economic dispatch framework are applied to the Electric Reliability Council of Texas (ERCOT) equivalent 24- bus system. Compared with persistence and autoregressive models, the first model suggests that cost savings from integration of wind power could be on the scale of tens of millions of dollars. For the second model, numerical simulations suggest that the overall generation cost can be reduced by up to 6.6% using look-ahead dispatch coupled with spatio-temporal wind forecast as compared with dispatch with persistent wind forecast model.

Zhu, Xinxin

2013-08-01T23:59:59.000Z

154

Solar forecasting review  

E-Print Network (OSTI)

Online 24-h solar power forecasting based on weather typeweather observations at blue hill massachusetts,” Solarof weather patterns on the intensity of solar irradiance;

Inman, Richard Headen

2012-01-01T23:59:59.000Z

155

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

156

forecast | OpenEI  

Open Energy Info (EERE)

Browse Upload data GDR Community Login | Sign Up Search Facebook icon Twitter icon forecast Dataset Summary Description The EIA's annual energy outlook (AEO) contains yearly...

157

Seasonal tropical cyclone forecasts  

E-Print Network (OSTI)

Seasonal forecasts of tropical cyclone activity in various regions have been developed since the first attempts in the early 1980s by Neville

Suzana J. Camargo; Anthony G. Barnston; Philip J. Klotzbach; Christopher W. Landsea

2007-01-01T23:59:59.000Z

158

Probabilistic Forecasts from the National Digital Forecast Database  

Science Conference Proceedings (OSTI)

The Bayesian processor of forecast (BPF) is developed for a continuous predictand. Its purpose is to process a deterministic forecast (a point estimate of the predictand) into a probabilistic forecast (a distribution function, a density function, ...

Roman Krzysztofowicz; W. Britt Evans

2008-04-01T23:59:59.000Z

159

Global and Local Skill Forecasts  

Science Conference Proceedings (OSTI)

A skill forecast gives the probability distribution for the error in a forecast. Statistically, Well-founded skill forecasting methods have so far only been applied within the context of simple models. In this paper, the growth of analysis errors ...

P. L. Houtekamer

1993-06-01T23:59:59.000Z

160

Distortion Representation of Forecast Errors  

Science Conference Proceedings (OSTI)

Forecast error is decomposed into three components, termed displacement error, amplitude error, mid residual error, respectively. Displacement error measures how much of the forecast error can be accounted for by moving the forecast to best fit ...

Ross N. Hoffman; Zheng Liu; Jean-Francois Louis; Christopher Grassoti

1995-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Composite forecasting in commodity systems  

E-Print Network (OSTI)

Paper No. COMPOSI1E FORECASTING IN CO/Yt.flDITI SYSTfu\\1S1980 .i CfIAPTER COMPOSITE FORECASTING IN COMMOOITY SYSTEMS*to utilizeeconometric .modelsfor forecasting ! ,urposes. The

Johnson, Stanley R; Rausser, Gordon C.

1980-01-01T23:59:59.000Z

162

Arnold Schwarzenegger INTEGRATED FORECAST AND  

E-Print Network (OSTI)

Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN; the former with primary contributions in the areas of climate and hydrologic forecasting and the latter Service (NWS) California Nevada River Forecast Center (CNRFC), the California Department of Water

163

CONSULTANT REPORT DEMAND FORECAST EXPERT  

E-Print Network (OSTI)

CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy

164

Does the term structure forecast  

E-Print Network (OSTI)

provides more accurate forecasts of real consumption growth14. Harvey, C.R. (1989): \\Forecasts of economic growth fromC.R. (1993): \\Term structure forecasts economic growth", Fi-

Berardi, Andrea; Torous, Walter

2002-01-01T23:59:59.000Z

165

Assumptions to the Annual Energy Outlook 2001 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for

166

Assumptions to the Annual Energy Outlook 2002 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for

167

Assumptions to the Annual Energy Outlook 2002 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).117 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration,

168

Assumptions to the Annual Energy Outlook 2001 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).112 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration,

169

Forecasting photovoltaic array power production subject to mismatch losses  

Science Conference Proceedings (OSTI)

The development of photovoltaic (PV) energy throughout the world this last decade has brought to light the presence of module mismatch losses in most PV applications. Such power losses, mainly occasioned by partial shading of arrays and differences in PV modules, can be reduced by changing module interconnections of a solar array. This paper presents a novel method to forecast existing PV array production in diverse environmental conditions. In this approach, field measurement data is used to identify module parameters once and for all. The proposed method simulates PV arrays with adaptable module interconnection schemes in order to reduce mismatch losses. The model has been validated by experimental results taken on a 2.2 kW{sub p} plant, with three different interconnection schemes, which show reliable power production forecast precision in both partially shaded and normal operating conditions. Field measurements show interest in using alternative plant configurations in PV systems for decreasing module mismatch losses. (author)

Picault, D.; Raison, B.; Bacha, S. [Grenoble Electrical Engineering Laboratory (G2Elab), 961, rue Houille Blanche BP 46, 38402 St Martin d'Heres (France); de la Casa, J.; Aguilera, J. [Grupo de Investigacion IDEA, Departamento de Electronica, Escuela Politecnica Superior, Universidad de Jaen, Campus Las Lagunillas, 23071 Jaen (Spain)

2010-07-15T23:59:59.000Z

170

Coefficients for Debiasing Forecasts  

Science Conference Proceedings (OSTI)

Skill-score decompositions can be used to analyze the effects of bias on forecasting skill. However, since bias terms are typically squared, and bias is measured in skill-score units rather than in units of the forecasts, such decompositions only ...

Thomas R. Stewart; Patricia Reagan-Cirincione

1991-08-01T23:59:59.000Z

171

Evaluating Point Forecasts  

E-Print Network (OSTI)

Typically, point forecasting methods are compared and assessed by means of an error measure or scoring function, such as the absolute error or the squared error. The individual scores are then averaged over forecast cases, to result in a summary measure of the predictive performance, such as the mean absolute error or the (root) mean squared error. I demonstrate that this common practice can lead to grossly misguided inferences, unless the scoring function and the forecasting task are carefully matched. Effective point forecasting requires that the scoring function be specified ex ante, or that the forecaster receives a directive in the form of a statistical functional, such as the mean or a quantile of the predictive distribution. If the scoring function is specified ex ante, the forecaster can issue the optimal point forecast, namely, the Bayes rule. If the forecaster receives a directive in the form of a functional, it is critical that the scoring function be consistent for it, in the sense that the expect...

Gneiting, Tilmann

2009-01-01T23:59:59.000Z

172

Forecasters ’ Objectives and Strategies ?  

E-Print Network (OSTI)

This chapter develops a unified modeling framework for analyzing the strategic behavior of forecasters. The theoretical model encompasses reputational objectives, competition for the best accuracy, and bias. Also drawing from the extensive literature on analysts, we review the empirical evidence on strategic forecasting and illustrate how our model can be structurally estimated.

Iván Marinovic; Marco Ottaviani; Peter Norman Sřrensen

2011-01-01T23:59:59.000Z

173

Essays on macroeconomics and forecasting  

E-Print Network (OSTI)

This dissertation consists of three essays. Chapter II uses the method of structural factor analysis to study the effects of monetary policy on key macroeconomic variables in a data rich environment. I propose two structural factor models. One is the structural factor augmented vector autoregressive (SFAVAR) model and the other is the structural factor vector autoregressive (SFVAR) model. Compared to the traditional vector autogression (VAR) model, both models incorporate far more information from hundreds of data series, series that can be and are monitored by the Central Bank. Moreover, the factors used are structurally meaningful, a feature that adds to the understanding of the �black box� of the monetary transmission mechanism. Both models generate qualitatively reasonable impulse response functions. Using the SFVAR model, both the �price puzzle� and the �liquidity puzzle� are eliminated. Chapter III employs the method of structural factor analysis to conduct a forecasting exercise in a data rich environment. I simulate out-of-sample real time forecasting using a structural dynamic factor forecasting model and its variations. I use several structural factors to summarize the information from a large set of candidate 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 forecasting models compared to alternatives that include univariate autoregression (AR) model, the VAR model and Stock and Watson�s (2002) models, especially when forecasting real variables. In chapter IV, we measure U.S. technology shocks by implementing a dual approach, which is based on more reliable price data instead of aggregate quantity data. By doing so, we find the relative volatility of technology shocks and the correlation between output fluctuation and technology shocks to be much smaller than those revealed in most real-business-cycle (RBC) studies. Our results support the findings of Burnside, Eichenbaum and Rebelo (1996), who showed that the correlation between technology shocks and output is exaggerated in the RBC literature. This suggests that one should examine other sources of fluctuations for a better understanding of the business cycle phenomena.

Liu, Dandan

2005-08-01T23:59:59.000Z

174

Developing electricity forecast web tool for Kosovo market  

Science Conference Proceedings (OSTI)

In this paper is presented a web tool for electricity forecast for Kosovo market for the upcoming ten years. The input data i.e. electricity generation capacities, demand and consume are taken from the document "Kosovo Energy Strategy 2009-2018" compiled ... Keywords: .NET, database, electricity forecast, internet, simulation, web

Blerim Rexha; Arben Ahmeti; Lule Ahmedi; Vjollca Komoni

2011-02-01T23:59:59.000Z

175

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST  

E-Print Network (OSTI)

Policy Report, over the entire forecast period, primarily because both weather-adjusted peak and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, California Solar Initiative. #12;ii #12

176

A New Verification Score for Public Forecasts  

Science Conference Proceedings (OSTI)

CREF, a new verification score for public forecasts, is introduced. This verification score rewards a forecaster who forecasts a rare event accurately. CREF was used to verify local forecasts at the Weather Service Forecast Office (WSFO) in ...

Dean P. Gulezian

1981-02-01T23:59:59.000Z

177

Forecasting technology costs via the Learning Curve - Myth or Magic?  

E-Print Network (OSTI)

is generally considered to be traditional fossil fuel power stations, hence making a further assumption that such a value for cost can be forecasted). In situations where niche markets exist (for example solar PV electricity for remote areas or hand held... Solar PV provides a good example of the use and dangers of using experience curves to forecast future costs of an energy technology. It is a good example since solar PV modules are generally accessed by an international market allowing for worldwide...

Alberth, Stephan

178

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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.

179

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint  

Science Conference Proceedings (OSTI)

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

180

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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.

Note: This page contains sample records for the topic "module generates forecasts" 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

NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS  

E-Print Network (OSTI)

· NATIONAL AND GLOBAL FORECASTS · WEST VIRGINIA PROFILES AND FORECASTS · ENERGY · HEALTHCARE Industry Insight: West Virginia Fiscal Forecast 34 CHAPTER 4: WEST ViRGiNiA'S 35 COUNTiES AND MSAs West Forecast Summary 2 CHAPTER 1: THE UNiTED STATES ECONOMY Figure 1.1: United States Real GDP Growth 3 Figure

Mohaghegh, Shahab

182

APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY  

E-Print Network (OSTI)

1 APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY Rick Katz.isse.ucar.edu/HP_rick/dmuu.pdf #12;2 QUOTES ON USE OF PROBABILITY FORECASTS · Lao Tzu (Chinese Philosopher) "He who knows does and Value of Probability Forecasts (4) Cost-Loss Decision-Making Model (5) Simulation Example (6) Economic

Katz, Richard

183

Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts  

Reports and Publications (EIA)

The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

Information Center

2010-06-01T23:59:59.000Z

184

Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumption to the Annual Energy Outlook Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2004, DOE/EIA-M060(2004) (Washington, DC, 2004). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of capacity utilization of mines, mining capacity, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

185

Why are survey forecasts superior to model forecasts?  

E-Print Network (OSTI)

We investigate two characteristics of survey forecasts that are shown to contribute to their superiority over purely model-based forecasts. These are that the consensus forecasts incorporate the effects of perceived changes in the long-run outlook, as well as embodying departures from the path toward the long-run expectation. Both characteristics on average tend to enhance forecast accuracy. At the level of the individual forecasts, there is scant evidence that the second characteristic enhances forecast accuracy, and the average accuracy of the individual forecasts can be improved by applying a mechanical correction.

Michael P. Clements; Michael P. Clements

2010-01-01T23:59:59.000Z

186

LOAD FORECASTING Eugene A. Feinberg  

E-Print Network (OSTI)

's electricity price forecasting model, produces forecast of gas demand consistent with electric load. #12Gas demand Council's Market Price of Electricity Forecast Natural GasDemand Electric Load Aggregating Natural between the natural gas and electricity and new uses of natural gas emerge. T natural gas forecasts

Feinberg, Eugene A.

187

Demand Forecast INTRODUCTION AND SUMMARY  

E-Print Network (OSTI)

Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required of any forecast of electricity demand and developing ways to reduce the risk of planning errors that could arise from this and other uncertainties in the planning process. Electricity demand is forecast

188

Forecasting Electricity Demand by Time Series Models  

Science Conference Proceedings (OSTI)

Electricity demand is one of the most important variables required for estimating the amount of additional capacity required to ensure a sufficient supply of energy. Demand and technological losses forecasts can be used to control the generation and distribution of electricity more efficiently. The aim of this paper is to utilize time series model

E. Stoimenova; K. Prodanova; R. Prodanova

2007-01-01T23:59:59.000Z

189

Factors Driving Prices & Forecast  

Gasoline and Diesel Fuel Update (EIA)

This spread is a function of the balance between demand and fresh supply (production and net imports). Finally I will discuss the current forecast for distillate prices this winter...

190

Modeling and Forecasting Aurora  

Science Conference Proceedings (OSTI)

Modeling the physical processes needed for forecasting space-weather events requires multiscale modeling. This article discusses several modelsresearchers use to treat the various auroral processes that influence space weather.

Dirk Lummerzheim

2007-01-01T23:59:59.000Z

191

Valuing Climate Forecast Information  

Science Conference Proceedings (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

192

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 12 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS 27 data.

193

EIA-Assumptions to the Annual Energy Outlook - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2007 Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

194

Regional Ensemble Forecasts Using the Ensemble Transform Technique  

Science Conference Proceedings (OSTI)

A computationally inexpensive ensemble transform (ET) method for generating high-resolution initial perturbations for regional ensemble forecasts is introduced. The method provides initial perturbations that (i) have an initial variance ...

Craig H. Bishop; Teddy R. Holt; Jason Nachamkin; Sue Chen; Justin G. McLay; James D. Doyle; William T. Thompson

2009-01-01T23:59:59.000Z

195

Informing Hydrometric Network Design for Statistical Seasonal Streamflow Forecasts  

Science Conference Proceedings (OSTI)

A hydrometric network design approach is developed for enhancing statistical seasonal streamflow forecasts. The approach employs gridded, model-simulated water balance variables as predictors in equations generated via principal components ...

Eric A. Rosenberg; Andrew W. Wood; Anne C. Steinemann

2013-10-01T23:59:59.000Z

196

Ensemble Forecasting at NCEP and the Breeding Method  

Science Conference Proceedings (OSTI)

The breeding method has been used to generate perturbations for ensemble forecasting at the National Centers for Environmental Prediction (formerly known as the National Meteorological Center) since December 1992. At that time a single breeding ...

Zoltan Toth; Eugenia Kalnay

1997-12-01T23:59:59.000Z

197

Improving Multiseason Forecasts of North Atlantic Hurricane Activity  

Science Conference Proceedings (OSTI)

Hurricanes cause drastic social problems as well as generate huge economic losses. A reliable forecast of the level of hurricane activity covering the next several seasons has the potential to mitigate against such losses through improvements in ...

James B. Elsner; Thomas H. Jagger; Michael Dickinson; Dail Rowe

2008-03-01T23:59:59.000Z

198

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

this “hybrid” NYMEX-EIA gas price projection still does notcomparison with fixed- price renewable generation (becauseonly a portion of the gas price forecast – through 2010 –

Bolinger, Mark; Wiser, Ryan

2005-01-01T23:59:59.000Z

199

Forecasting in the Presence of Level Shifts  

E-Print Network (OSTI)

accuracy. Journal of Forecasting 19 : 537-560. Hamilton JD.430. Harvey AC. 1989. Forecasting, structural time seriesMH, Timmermann A. 1994. Forecasting stock returns: An

Smith, Aaron

2004-01-01T23:59:59.000Z

200

Multivariate Forecast Evaluation And Rationality Testing  

E-Print Network (OSTI)

1062—1088. MULTIVARIATE FORECASTS Chaudhuri, P. (1996): “OnKingdom. MULTIVARIATE FORECASTS Kirchgässner, G. , and U. K.2005): “Estimation and Testing of Forecast Rationality under

Komunjer, Ivana; OWYANG, MICHAEL

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

FROM ANALYSTS ' EARNINGS FORECASTS  

E-Print Network (OSTI)

We examine the accuracy and bias of intrinsic equity prices estimated from three accounting-based valuation models using analyst’s earnings forecasts over a four-year horizon. The models are: (a) the earnings capitalization model, (b) the residual income model without a terminal value, and (c) the residual income model with a terminal value that assumes residual income will grow beyond the horizon at a constant rate determined from the expected residual income growth rate over the forecast horizon. Our analysis is based on valuation errors that are calculated by comparing estimated prices to actual prices. We contribute to the literature by examining whether: (i) the analysts ’ earnings forecasts convey information about value beyond that conveyed by current earnings, book value and dividends, (ii) the use of firm specific growth rates in terminal value calculations results in more unbiased and accurate valuations than the use of constant growth rates, and (iii) different models perform better under different ex-ante conditions. We find that analysts ’ earnings forecasts convey information about value beyond that conveyed by current earnings, book values and dividends. Each of the models that we used has valuation errors that decline monotonically as the horizon increases implying that earnings forecasts at each horizon convey new value relevant information. We cannot find a clear advantage to using firm specific growth rates instead of a constant rate of 4 % across all sample

Theodore Sougiannis; Takashi Yaekura

2000-01-01T23:59:59.000Z

202

Operational forecasting based on a modified Weather Research and Forecasting model  

DOE Green Energy (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

203

European Union Wind Energy Forecasting Model Development and Testing: U.S. Department of Energy -- EPRI Wind Turbine Verification Pr ogram  

Science Conference Proceedings (OSTI)

Wind forecasting can increase the strategic and market values of wind power from large wind facilities. This report summarizes the results of the European Union (EU) wind energy forecasting project and performance testing of the EU wind forecasting model. The testing compared forecast and observed wind speed and generation data from U.S. wind facilities.

1999-12-15T23:59:59.000Z

204

Comparison of Wind Power and Load Forecasting Error Distributions: Preprint  

DOE Green Energy (OSTI)

The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

2012-07-01T23:59:59.000Z

205

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast

206

Monthly generator capacity factor data now available by ...  

U.S. Energy Information Administration (EIA)

weather; gasoline; capacity; exports; nuclear; forecast; ... Solar generators—particularly solar thermal—operate at a minimum during winter months, ...

207

California Wind Energy Forecasting System Development and Testing, Phase 1: Initial Testing  

Science Conference Proceedings (OSTI)

Wind energy forecasting uses sophisticated numerical weather forecasting and wind plant power generation models to predict the hourly energy generation of a wind power plant up to 48 hours in advance. As a result, it has great potential to address the needs of the California Independent System Operator (ISO) and the wind plant operators, as well as power marketers and buyers and utility system dispatch personnel. This report gives the results of 28 days of testing of wind energy forecasting at a Californ...

2003-01-31T23:59:59.000Z

208

Consensus Coal Production Forecast for  

E-Print Network (OSTI)

Consensus Coal Production Forecast for West Virginia 2009-2030 Prepared for the West Virginia Summary 1 Recent Developments 2 Consensus Coal Production Forecast for West Virginia 10 Risks References 27 #12;W.Va. Consensus Coal Forecast Update 2009 iii List of Tables 1. W.Va. Coal Production

Mohaghegh, Shahab

209

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

210

Forecast Technical Document Technical Glossary  

E-Print Network (OSTI)

Forecast Technical Document Technical Glossary A document defining some of the terms used in the 2011 Production Forecast technical documentation. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the Forecast documentation. In some cases, the terms and the descriptions are "industry standard", in others

211

Forecast Technical Document Tree Species  

E-Print Network (OSTI)

Forecast Technical Document Tree Species A document listing the tree species included in the 2011 Production Forecast Tom Jenkins Justin Gilbert Ewan Mackie Robert Matthews #12;PF2011 ­ List of tree species The following is the list of species used within the Forecast System. Species are ordered alphabetically

212

3, 21452173, 2006 Probabilistic forecast  

E-Print Network (OSTI)

HESSD 3, 2145­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page for probabilistic forecasts of continuous hydrological variables F. Laio and S. Tamea DITIC ­ Department­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page Abstract Introduction

Paris-Sud XI, Université de

213

4, 189212, 2007 Forecast and  

E-Print Network (OSTI)

OSD 4, 189­212, 2007 Forecast and analysis assessment through skill scores M. Tonani et al. Title Science Forecast and analysis assessment through skill scores M. Tonani 1 , N. Pinardi 2 , C. Fratianni 1 Forecast and analysis assessment through skill scores M. Tonani et al. Title Page Abstract Introduction

Paris-Sud XI, Université de

214

FINANCIAL FORECASTING USING GENETIC ALGORITHMS  

E-Print Network (OSTI)

predecessors to forecast stock prices and manage portfolios for approximately 3 years.) We examineFINANCIAL FORECASTING USING GENETIC ALGORITHMS SAM MAHFOUD and GANESH MANI LBS Capital Management entitled Genetic Algorithms for Inductive Learning). Time-series forecasting is a special type

Boetticher, Gary D.

215

Forecast of auroral activity  

Science Conference Proceedings (OSTI)

A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting

A. T. Y. Lui

2004-01-01T23:59:59.000Z

216

Wind forecasting objectives for utility schedulers and energy traders  

DOE Green Energy (OSTI)

The wind energy industry and electricity producers can benefit in a number of ways from increased wind forecast accuracy. Higher confidence in the reliability of wind forecasts can help persuade an electric utility to increase the penetration of wind energy into its operating system and to augment the capacity value of wind electric generation. Reliable forecasts can also assist daily energy traders employed by utilities in marketing the available and anticipated wind energy to power pools and other energy users. As the number of utilities with wind energy experience grows, and wind energy penetration levels increase, the need for reliable wind forecasts will likely grow as well. This period of wind energy growth also coincides with advances in computer weather prediction technology that could lead to more accurate wind forecasts. Thus, it is important to identify the type of forecast information needed by utility schedulers and energy traders. This step will help develop approaches to the challenge of wind forecasting that will result in useful products being supplied to utilities or other energy generating entities. This paper presents the objectives, approach, and current findings of a US Department of Energy National Renewable Energy Laboratory (DOE/NREL) initiative to develop useful wind forecasting tools for utilities involved with wind energy generation. The focus of this initiative thus far has been to learn about the needs of prospective utility users. NREL representatives conducted a series of onsite interviews with key utility staff, usually schedulers and research planners, at seven US utilities. The purpose was to ascertain information on actual scheduling and trading procedures, and how utilities could integrate wind forecasting into these activities.

Schwartz, M.N. [National Renewable Energy Lab., Golden, CO (United States); Bailey, B.H. [AWS Scientific, Inc., Albany, NY (United States)

1998-05-01T23:59:59.000Z

217

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

218

Short-Termed Integrated Forecasting System: 1993 Model documentation report  

Science Conference Proceedings (OSTI)

The purpose of this report is to define the Short-Term Integrated Forecasting System (STIFS) and describe its basic properties. The Energy Information Administration (EIA) of the US Energy Department (DOE) developed the STIFS model to generate short-term (up to 8 quarters), monthly forecasts of US supplies, demands, imports exports, stocks, and prices of various forms of energy. The models that constitute STIFS generate forecasts for a wide range of possible scenarios, including the following ones done routinely on a quarterly basis: A base (mid) world oil price and medium economic growth. A low world oil price and high economic growth. A high world oil price and low economic growth. This report is written for persons who want to know how short-term energy markets forecasts are produced by EIA. The report is intended as a reference document for model analysts, users, and the public.

Not Available

1993-05-01T23:59:59.000Z

219

Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint  

DOE Green Energy (OSTI)

One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

2013-10-01T23:59:59.000Z

220

Short-term wind speed forecasting based on a hybrid model  

Science Conference Proceedings (OSTI)

Wind power is currently one of the types of renewable energy with a large generation capacity. However, operation of wind power generation is very challenging because of the intermittent and stochastic nature of the wind speed. Wind speed forecasting ... Keywords: Forecasting, RBF neural networks, Seasonal adjustment, Wavelet transform, Wind speed

Wenyu Zhang, Jujie Wang, Jianzhou Wang, Zengbao Zhao, Meng Tian

2013-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Texas Wind Energy Forecasting System Development and Testing: Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

Wind energy forecasting systems are expected to support system operation in cases where wind generation contributes more than a few percent of total generating capacity. This report presents final results from the Texas Wind Energy Forecasting System Development and Testing Project at a 75-MW wind project in west Texas.

2004-09-30T23:59:59.000Z

222

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,

223

EIA model documentation: Electricity market module - electricity fuel dispatch  

Science Conference Proceedings (OSTI)

This report documents the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM) as it was used for EIA`s Annual Energy Outlook 1997. It replaces previous documentation dated March 1994 and subsequent yearly update revisions. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This document serves four purposes. First, it is a reference document providing a detailed description of the model for reviewers and potential users of the EFD including energy experts at the Energy Information Administration (EIA), other Federal agencies, state energy agencies, private firms such as utilities and consulting firms, and non-profit groups such as consumer and environmental groups. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports. Third, it facilitates continuity in model development by providing documentation which details model enhancements that were undertaken for AE097 and since the previous documentation. Last, because the major use of the EFD is to develop forecasts, this documentation explains the calculations, major inputs and assumptions which were used to generate the AE097.

NONE

1997-01-01T23:59:59.000Z

224

Critical Operating Constraints Forecast-- Functional Specification  

Science Conference Proceedings (OSTI)

Critical operating constraints that could result in curtailments of load may occur in a transmission grid with areas of potential generation deficit and limited transmission import capacities. In such situations, it is crucial that the grid operators have a tool to predict when and where critical operating constraints would occur. This report describes the functional specification of such a decision support tool, called the COCF (Critical Operating Constraint Forecast).

2008-03-04T23:59:59.000Z

225

Assumptions to the Annual Energy Outlook - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumption to the Annual Energy Outlook Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).109 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

226

Modulating lignin in plants  

DOE Patents (OSTI)

Materials and methods for modulating (e.g., increasing or decreasing) lignin content in plants are disclosed. For example, nucleic acids encoding lignin-modulating polypeptides are disclosed as well as methods for using such nucleic acids to generate transgenic plants having a modulated lignin content.

Apuya, Nestor; Bobzin, Steven Craig; Okamuro, Jack; Zhang, Ke

2013-01-29T23:59:59.000Z

227

Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures  

E-Print Network (OSTI)

Forecasting Dangerous Inmate Misconduct: An Applications ofidentify with useful forecasting skill the very few inmatescontribute substantially to forecasting skill necessarily

Berk, Richard; Kriegler, Brian; Baek, Jong-Ho

2005-01-01T23:59:59.000Z

228

Information and Inference in Econometrics: Estimation, Testing and Forecasting  

E-Print Network (OSTI)

Application: Forecasting Equity Premium . . . . . . . . . .2.6.1 Forecasting4 Forecasting Using Supervised Factor Models 4.1

Tu, Yundong

2012-01-01T23:59:59.000Z

229

Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures  

E-Print Network (OSTI)

Forecasting Dangerous Inmate Misconduct: An Applications ofidentify with useful forecasting skill the very few inmatescontribute substantially to forecasting skill necessarily

Richard A. Berk; Brian Kriegler; Jong-Ho Baek

2011-01-01T23:59:59.000Z

230

Development and testing of improved statistical wind power forecasting methods.  

DOE Green Energy (OSTI)

Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

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

2011-12-06T23:59:59.000Z

231

Management Earnings Forecasts and Value of Analyst Forecast Revisions  

E-Print Network (OSTI)

Prior studies evaluate the relative importance of the sources of value that financial analysts bring to the market based on the price impact of forecast revisions over the event time. We find that management earnings forecasts influence the timing and precision of analyst forecasts. More importantly, evidence suggests that prior studies ’ finding of weaker (stronger) stock-price responses to forecast revisions in the period immediately after (before) the prior-quarter earnings announcement is likely to be the artifact of a temporal pattern of management earnings forecasts over the event time. To the extent that management earnings forecasts are public disclosures, our results suggest that the relative importance of analysts ' information discovery role documented in prior studies is likely to be overstated.

Yongtae Kim; Minsup Song

2013-01-01T23:59:59.000Z

232

EIA-Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2007 Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2007, DOE/EIA-M060(2007) (Washington, DC, 2007). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

233

Chapter 11 Forecasting breaks and forecasting during breaks  

E-Print Network (OSTI)

Success in accurately forecasting breaks requires that they are predictable from relevant information available at the forecast origin using an appropriate model form, which can be selected and estimated before the break. To clarify the roles of these six necessary conditions, we distinguish between the information set for ‘normal forces ’ and the one for ‘break drivers’, then outline sources of potential information. Relevant non-linear, dynamic models facing multiple breaks can have more candidate variables than observations, so we discuss automatic model selection. As a failure to accurately forecast breaks remains likely, we augment our strategy by modelling breaks during their progress, and consider robust forecasting devices.

Jennifer L. Castle; Nicholas W. P. Fawcett; David F. Hendry

2011-01-01T23:59:59.000Z

234

MODULATION OF LOW ENERGY BEAM TO GENERATE PREDEFINED BUNCH TRAINS FOR THE NSLS-II TOP-OFF INJECTION  

SciTech Connect

The NSLS II linac will produce a bunch train, 80-150 bunches long with 2 ns bunch spacing. Having the ability to tailor the bunch train can lead to the smaller bunch to bunch charge variation in the storage ring. A stripline is planned to integrate into the linac baseline to achieve this tailoring. The stripline must have a fast field rise and fall time to tailor each bunch. The beam dynamics is minimally affected by including the extra space for the stripline. This paper discusses the linac beam dynamics with stripline, and the optimal design of the stripline. A stripline is to be integrated in the linac to match the storage ring uniform bunch charge requirement, which simplifies the gun pulser electronics and looses the edge uniform requirement. It is located at low energy to lower the stripline power supply requirement and limit the dumped electron radiation. By turning off the stripline, the beam dynamics through linac is comparable with the baseline design. More advanced ideas can be explored. If a DC corrector along with the stripline is used, the core bunch trains gets kick from the stripline while the head and the tail of bunch train just gets a DC kick. The stripline power supply waveform is a single flat top waveform with fast rise and drop and the pulse length is {approx}200 ns long or 100 bunches, which may be easier from the power supply view point. We are also considering the bunch by bunch charge manipulation to match the storage ring uniform bunch charge distribution requirement. By modulating the flat top waveform at 250 MHz with adjustable amplitude, each the bunch center is either at 45 degree or 135 degree. Only the head or tail of the bunch is trimmed out. Although each bunch center deviation from idea center is very different at low energy, it is gradually minimized with beam energy increase.

Wang, G.M.; Cheng, W.X.; Shaftan, T.; Fliller, R.; Heese, R.; Rose, J.

2011-03-28T23:59:59.000Z

235

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

E-Print Network (OSTI)

Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model developed for industrial energy analysis at the Pacific Northwest National Laboratory. Although the results are mixed, generally ITEMS show greater penetration of energy efficient technologies and thus lower energy use, even though the business as usual forecasts for ITEMS uses a higher discount rate than NEMS uses.

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

2000-04-01T23:59:59.000Z

236

Linking the Eta Model with the Community Multiscale Air Quality (CMAQ) Modeling System to Build a National Air Quality Forecasting System  

Science Conference Proceedings (OSTI)

NOAA and the U.S. Environmental Protection Agency (EPA) have developed a national air quality forecasting (AQF) system that is based on numerical models for meteorology, emissions, and chemistry. The AQF system generates gridded model forecasts ...

Tanya L. Otte; George Pouliot; Jonathan E. Pleim; Jeffrey O. Young; Kenneth L. Schere; David C. Wong; Pius C. S. Lee; Marina Tsidulko; Jeffery T. McQueen; Paula Davidson; Rohit Mathur; Hui-Ya Chuang; Geoff DiMego; Nelson L. Seaman

2005-06-01T23:59:59.000Z

237

Forecasting Uncertain Hotel Room Demand  

E-Print Network (OSTI)

Economic systems are characterized by increasing uncertainty in their dynamics. This increasing uncertainty is likely to incur bad decisions that can be costly in financial terms. This makes forecasting of uncertain economic variables an instrumental activity in any organization. This paper takes the hotel industry as a practical application of forecasting using the Holt-Winters method. The problem here is to forecast the uncertain demand for rooms at a hotel for each arrival day. Forecasting is part of hotel revenue management system whose objective is to maximize the revenue by making decisions regarding when to make rooms available for customers and at what price. The forecast approach discussed in this paper is based on quantitative models and does not incorporate management expertise. Even though, forecast results are found to be satisfactory for certain days, this is not the case for other arrival days. It is believed that human judgment is important when dealing with ...

Mihir Rajopadhye Mounir; Mounir Ben Ghaliay; Paul P. Wang; Timothy Baker; Craig V. Eister

2001-01-01T23:59:59.000Z

238

Evaluating Covariance Matrix Forecasts in a Value-at-Risk Framework  

E-Print Network (OSTI)

: Covariance matrix forecasts of financial asset returns are an important component of current practice in financial risk management. A wide variety of models are available for generating such forecasts. In this paper, we evaluate the relative performance of different covariance matrix forecasts using standard statistical loss functions and a value-at-risk (VaR) framework. Using a foreign exchange portfolio, we find covariance matrix forecasts generated from option prices perform best under statistical loss functions, such as mean-squared error. Within a VaR framework, the relative performance of covariance matrix forecasts depends greatly on the VaR models' distributional assumptions. Of the forecasts examined, simple specifications, such as exponentially-weighted moving averages of past observations, perform best with regard to the magnitude of VaR exceptions and regulatory capital requirements. Our results provide empirical support for the commonly-used VaR models based on simple c...

Jose A. Lopez; Christian A. Walter

2001-01-01T23:59:59.000Z

239

Forecast Technical Document Growing Stock Volume  

E-Print Network (OSTI)

Forecast Technical Document Growing Stock Volume Forecasts A document describing how growing stock (`standing') volume is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Growing stock volume forecasts Background A forecast of standing volume (or

240

WRF-Fire: Coupled Weather–Wildland Fire Modeling with the Weather Research and Forecasting Model  

Science Conference Proceedings (OSTI)

A wildland fire-behavior module, named WRF-Fire, was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire-behavior model that is two-way coupled with the ...

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

commercial.gif (5196 bytes) commercial.gif (5196 bytes) The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings, however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

242

A survey on wind power ramp forecasting.  

DOE Green Energy (OSTI)

The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

2011-02-23T23:59:59.000Z

243

Forecasting of mine price for central Appalachian steam coal  

SciTech Connect

In reaction to Virginia's declining share of the steam coal market and the subsequent depression in southwest Virginia's economy, an optimization model of the central Appalachian steam coal market was developed. The input to the cost vector was the delivered cost of coal, which is comprised of the mine price (FOB) and transportation cost. One objective of the study was to develop a purchasing model that could be used to minimize the cost of coal procurement over a multi-period time span. The initial case study used a six-month period (7/86-12/86); this requires short-term, forecasts of the mine price of coal. Mine-cost equations and regression models were found to be inadequate for forecasting the mine price of coal. Instead forecasts were generated using modified time series models. This paper describes the application of classical time-series modeling to forecasting the mine price of coal in central Appalachia; in particular, the special modification to the classical methodology needed to generate short-term forecasts and their confidence limits and the need to take into account market-specific considerations such as the split between long-term contracts and the spot market. Special consideration is given to forecasting the spot market. 7 references, 4 figures, 3 tables.

Smith, M.L.

1988-01-01T23:59:59.000Z

244

Aviation forecasting and systems analyses  

SciTech Connect

The 9 papers in this report deal with the following areas: method of allocating airport runway slots; method for forecasting general aviation activity; air traffic control network-planning model based on second-order Markov chains; analyzing ticket-choice decisions of air travelers; assessing the safety and risk of air traffic control systems: risk estimation from rare events; forecasts of aviation fuel consumption in Virginia; estimating the market share of international air carriers; forecasts of passenger and air-cargo activity at Logan International Airport; and forecasting method for general aviation aircraft and their activity.

Geisinger, K.E.; Brander, J.R.G.; Wilson, F.R.; Kohn, H.M.; Polhemus, N.W.

1980-01-01T23:59:59.000Z

245

Studies of inflation and forecasting.  

E-Print Network (OSTI)

??This dissertation contains five research papers in the area of applied econometrics. The two broad themes of the research are inflation and forecasting. The first… (more)

Bermingham, Colin

2011-01-01T23:59:59.000Z

246

Application of Learning Fuzzy Inference Systems in Electricity Load Forecast  

E-Print Network (OSTI)

This paper highlights the results and applied techniques for the electricity load forecast competition organised by the European Network on Intelligent Technologies for Smart Adaptive Systems (www.eunite.org). The electricity load forecast problem is tackled in two di#erent stages by creating two di#erent models. The first model will predict the temperature and the second model uses the predicted temperature to forecast the maximum electricity load. For both model, learning fuzzy inference systems are applied. Initial fuzzy rules are generated and then the numerical data provided by Eastern Slovakian Electricity Corporation are used to learn the parameters of the learning fuzzy inference systems. The learning technique is applied for both temperature and load forecast.

Ahamd Lotfi

2001-01-01T23:59:59.000Z

247

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

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

248

Density Forecasting for Long-Term Peak Electricity Demand  

E-Print Network (OSTI)

Long-term electricity demand forecasting plays an important role in planning for future generation facilities and transmission augmentation. In a long-term context, planners must adopt a probabilistic view of potential peak demand levels. Therefore density forecasts (providing estimates of the full probability distributions of the possible future values of the demand) are more helpful than point forecasts, and are necessary for utilities to evaluate and hedge the financial risk accrued by demand variability and forecasting uncertainty. This paper proposes a new methodology to forecast the density of long-term peak electricity demand. Peak electricity demand in a given season is subject to a range of uncertainties, including underlying population growth, changing technology, economic conditions, prevailing weather conditions (and the timing of those conditions), as well as the general randomness inherent in individual usage. It is also subject to some known calendar effects due to the time of day, day of week, time of year, and public holidays. A comprehensive forecasting solution is described in this paper. First, semi-parametric additive models are used to estimate the relationships between demand and the driver variables, including temperatures, calendar effects and some demographic and economic variables. Then the demand distributions are forecasted by using a mixture of temperature simulation, assumed future economic scenarios, and residual bootstrapping. The temperature simulation is implemented through a new seasonal bootstrapping method with variable blocks. The proposed methodology has been used to forecast the probability distribution of annual and weekly peak electricity demand for South Australia since 2007. The performance of the methodology is evaluated by comparing the forecast results with the actual demand of the summer 2007–2008.

Rob J. Hyndman; Shu Fan

2009-01-01T23:59:59.000Z

249

Customer Response to Electricity Prices: Information to Support Wholesale Price Forecasting and Market Analysis  

Science Conference Proceedings (OSTI)

Understanding customer response to electricity price changes is critical to profitably managing a retail business, designing efficient wholesale power markets, and forecasting power prices for valuation of long-lived generating assets. This report packages the collective results of dozens of price response studies for use by forward price forecasters and power market analysts in forecasting loads, revenues, and the benefits of time-varying prices more accurately. In specific, the report describes key mea...

2001-11-30T23:59:59.000Z

250

Residential Sector Demand Module 1998, Model Documentation  

Reports and Publications (EIA)

This is the fourth edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy Modeling System (NEMS). It reflects changes made to themodule over the past year for the Annual Energy Outlook 1998. Since last year, severalnew end-use services were added to the module, including: Clothes washers,dishwashers, furnace fans, color televisions, and personal computers. Also, as with allNEMS modules, the forecast horizon has been extended to the year 2020.

John H. Cymbalsky

1998-01-01T23:59:59.000Z

251

Evaluating Density Forecasts: Forecast Combinations, Model Mixtures, Calibration and Sharpness  

E-Print Network (OSTI)

In a recent article Gneiting, Balabdaoui and Raftery (JRSSB, 2007) propose the criterion of sharpness for the evaluation of predictive distributions or density forecasts. They motivate their proposal by an example in which standard evaluation procedures based on probability integral transforms cannot distinguish between the ideal forecast and several competing forecasts. In this paper we show that their example has some unrealistic features from the perspective of the time-series forecasting literature, hence it is an insecure foundation for their argument that existing calibration procedures are inadequate in practice. We present an alternative, more realistic example in which relevant statistical methods, including information-based methods, provide the required discrimination between competing forecasts. We conclude that there is no need for a subsidiary criterion of sharpness.

James Mitchell; Kenneth F. Wallis

2008-01-01T23:59:59.000Z

252

On the Prediction of Forecast Skill  

Science Conference Proceedings (OSTI)

Using 10-day forecast 500 mb height data from the last 7 yr, the potential to predict the skill of numerical weather forecasts is discussed. Four possible predictor sets are described. The first, giving the consistency between adjacent forecasts, ...

T. N. Palmer; S. Tibaldi

1988-12-01T23:59:59.000Z

253

Equitable Skill Scores for Categorical Forecasts  

Science Conference Proceedings (OSTI)

Many skill scores used to evaluate categorical forecasts of discrete variables are inequitable, in the sense that constant forecasts of some events lead to better scores than constant forecasts of other events. Inequitable skill scores may ...

Lev S. Gandin; Allan H. Murphy

1992-02-01T23:59:59.000Z

254

Whither the Weather Analysis and Forecasting Process?  

Science Conference Proceedings (OSTI)

An argument is made that if human forecasters are to continue to maintain a skill advantage over steadily improving model and guidance forecasts, then ways have to be found to prevent the deterioration of forecaster skills through disuse. The ...

Lance F. Bosart

2003-06-01T23:59:59.000Z

255

Lagged Ensembles, Forecast Configuration, and Seasonal Predictions  

Science Conference Proceedings (OSTI)

An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) is presented. The focus of the analysis is on the construction of lagged ensemble forecasts ...

Mingyue Chen; Wanqiu Wang; Arun Kumar

256

Improving Forecast Communication: Linguistic and Cultural Considerations  

Science Conference Proceedings (OSTI)

One goal of weather and climate forecasting is to inform decision making. Effective communication of forecasts to various sectors of the public is essential for meeting that goal, yet studies repeatedly show that forecasts are not well understood ...

Karen Pennesi

2007-07-01T23:59:59.000Z

257

Lagged Ensembles, Forecast Configuration, and Seasonal Predictions  

Science Conference Proceedings (OSTI)

An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), is presented. The focus of the analysis is on the construction of lagged ensemble forecasts ...

Mingyue Chen; Wanqiu Wang; Arun Kumar

2013-10-01T23:59:59.000Z

258

Evaluation of errors in national energy forecasts.  

E-Print Network (OSTI)

??Energy forecasts are widely used by the U.S. government, politicians, think tanks, and utility companies. While short-term forecasts were reasonably accurate, medium and long-range forecasts… (more)

Sakva, Denys

2005-01-01T23:59:59.000Z

259

What Is the True Value of Forecasts?  

Science Conference Proceedings (OSTI)

Understanding the economic value of weather and climate forecasts is of tremendous practical importance. Traditional models that have attempted to gauge forecast value have focused on a best-case scenario, in which forecast users are assumed to ...

Antony Millner

2009-10-01T23:59:59.000Z

260

Diagnosing Forecast Errors in Tropical Cyclone Motion  

Science Conference Proceedings (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 "module generates forecasts" 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

Forecasting Electric Vehicle Costs with Experience Curves  

E-Print Network (OSTI)

April, 5. R 2~1. Dino. "Forecasting the Price Evolution of 1ElectromcProducts," Ioumal of Forecasting, ĄoL4, No I, 1985.costs and a set of forecasting tools that can be refined as

Lipman, Timonthy E.; Sperling, Daniel

2001-01-01T23:59:59.000Z

262

Probabilistic Verification of Monthly Temperature Forecasts  

Science Conference Proceedings (OSTI)

Monthly forecasting bridges the gap between medium-range weather forecasting and seasonal predictions. While such forecasts in the prediction range of 1–4 weeks are vital to many applications in the context of weather and climate risk management, ...

Andreas P. Weigel; Daniel Baggenstos; Mark A. Liniger; Frédéric Vitart; Christof Appenzeller

2008-12-01T23:59:59.000Z

263

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

264

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

265

A Forecast for the California Labor Market  

E-Print Network (OSTI)

issue for the state. A Forecast for the California Laborto Go? ” The UCLA Anderson Forecast for the Nation andAngeles: UCLA Anderson Forecast: Nation 1.1 – 1.9. Dhawan,

Mitchell, Daniel J. B.

2001-01-01T23:59:59.000Z

266

STAFF FORECAST OF 2007 PEAK STAFFREPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION STAFF FORECAST OF 2007 PEAK DEMAND STAFFREPORT June 2006 CEC-400.................................................................................. 9 Sources of Forecast Error....................................................................... .................11 Tables Table 1: Revised versus September 2005 Peak Demand Forecast ......................... 2

267

Operational Forecaster Uncertainty Needs and Future Roles  

Science Conference Proceedings (OSTI)

Key results of a comprehensive survey of U.S. National Weather Service operational forecast managers concerning the assessment and communication of forecast uncertainty are presented and discussed. The survey results revealed that forecasters are ...

David R. Novak; David R. Bright; Michael J. Brennan

2008-12-01T23:59:59.000Z

268

Calibration of Probabilistic Forecasts of Binary Events  

Science Conference Proceedings (OSTI)

Probabilistic forecasts of atmospheric variables are often given as relative frequencies obtained from ensembles of deterministic forecasts. The detrimental effects of imperfect models and initial conditions on the quality of such forecasts can ...

Cristina Primo; Christopher A. T. Ferro; Ian T. Jolliffe; David B. Stephenson

2009-03-01T23:59:59.000Z

269

CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST  

E-Print Network (OSTI)

1 CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST QUALITY: EVIDENCE FROM FRENCH IPOS Anis attributes, ownership retained, auditor quality, and underwriter reputation and management earnings forecast quality measured by management earnings forecast accuracy and bias. Using 117 French IPOs, we find

Paris-Sud XI, Université de

270

Forecasting women's apparel sales using mathematical  

E-Print Network (OSTI)

Forecasting women's apparel sales using mathematical modeling Celia Frank and Ashish Garg, USA Les Sztandera Philadelphia University, Philadelphia, PA, USA Keywords Apparel, Forecasting average (MA), auto- regression (AR), or combinations of them are used for forecasting sales. Since

Raheja, Amar

271

Calibration of Probabilistic Quantitative Precipitation Forecasts  

Science Conference Proceedings (OSTI)

From 1 August 1990 to 31 July 1995, the Weather Service Forecast Office in Pittsburgh prepared 6159 probabilistic quantitative precipitation forecasts. Forecasts were made twice a day for 24-h periods beginning at 0000 and 1200 UTC for two river ...

Roman Krzysztofowicz; Ashley A. Sigrest

1999-06-01T23:59:59.000Z

272

Evaluating Probabilistic Forecasts Using Information Theory  

Science Conference Proceedings (OSTI)

The problem of assessing the quality of an operational forecasting system that produces probabilistic forecasts is addressed using information theory. A measure of the quality of the forecasting scheme, based on the amount of a data compression ...

Mark S. Roulston; Leonard A. Smith

2002-06-01T23:59:59.000Z

273

Virtual Floe Ice Drift Forecast Model Intercomparison  

Science Conference Proceedings (OSTI)

Both sea ice forecast models and methods to measure their skill are needed for operational sea ice forecasting. Two simple sea ice models are described and tested here. Four different measures of skill are also tested. The forecasts from the ...

Robert W. Grumbine

1998-09-01T23:59:59.000Z

274

Ensemble Cloud Model Applications to Forecasting Thunderstorms  

Science Conference Proceedings (OSTI)

A cloud model ensemble forecasting approach is developed to create forecasts that describe the range and distribution of thunderstorm lifetimes that may be expected to occur on a particular day. Such forecasts are crucial for anticipating severe ...

Kimberly L. Elmore; David J. Stensrud; Kenneth C. Crawford

2002-04-01T23:59:59.000Z

275

The evolution of consensus in macroeconomic forecasting  

E-Print Network (OSTI)

When professional forecasters repeatedly forecast macroeconomic variables, their forecasts may converge over time towards a consensus. The evolution of consensus is analyzed with Blue Chip data under a parametric polynomial decay function that permits flexibility in the decay path. For the most part, this specification fits the data. We test whether forecast differences decay to zero at the same point in time for a panel of forecasters, and discuss possible explanations for this, along with its implications for studies using panels of forecasters.

Allan W. Gregory; James Yetman; Jel Codes C E; Robert Eggert; Fred Joutz

2004-01-01T23:59:59.000Z

276

Background pollution forecast over bulgaria  

Science Conference Proceedings (OSTI)

Both, the current level of air pollution studies and social needs in the country, are in a stage mature enough for creating Bulgarian Chemical Weather Forecasting and Information System The system is foreseen to provide in real time forecast of the spatial/temporal ...

D. Syrakov; K. Ganev; M. Prodanova; N. Miloshev; G. Jordanov; E. Katragkou; D. Melas; A. Poupkou; K. Markakis

2009-06-01T23:59:59.000Z

277

Frequency Dependence in Forecast Skill  

Science Conference Proceedings (OSTI)

A method is proposed to calculate measures of forecast skill for high, medium and low temporal frequency variations in the atmosphere. This method is applied to a series of 128 consecutive 1 to 10-day forecasts produced at NMC with their ...

H. M. van Den Dool; Suranjana Saha

1990-01-01T23:59:59.000Z

278

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

279

Improving Forecasting: A plea for historical retrospectives  

NLE Websites -- All DOE Office Websites (Extended Search)

Improving Forecasting: A plea for historical retrospectives Title Improving Forecasting: A plea for historical retrospectives Publication Type Journal Article Year of Publication...

280

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

Note: This page contains sample records for the topic "module generates forecasts" 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

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

282

Essays in International Macroeconomics and Forecasting  

E-Print Network (OSTI)

This dissertation contains three essays in international macroeconomics and financial time series forecasting. In the first essay, I show, numerically, that a two-country New-Keynesian Sticky Prices model, driven by monetary and productivity shocks, is capable of explaining the highly positive correlation across the industrialized countries' inflation even though their cross-country correlation in money growth rate is negligible. The structure of this model generates cross-country correlations of inflation, output and consumption that appear to closely correspond to the data. Additionally, this model can explain the internal correlation between inflation and output observed in the data. The second essay presents two important results. First, gains from monetary policy cooperation are different from zero when the elasticity of substitution between domestic and imported goods consumption is different from one. Second, when monetary policy is endogenous in a two-country model, the only Nash equilibria supported by this model are those that are symmetrical. That is, all exporting firms in both countries choose to price in their own currency, or all exporting firms in both countries choose to price in the importer's currency. The last essay provides both conditional and unconditional predictive ability evaluations of the aluminum futures contracts prices, by using five different econometric models, in forecasting the aluminum spot price monthly return 3, 15, and 27-months ahead for the sample period 1989.01-2010.10. From these evaluations, the best model in forecasting the aluminum spot price monthly return 3 and 15 months ahead is followed by a (VAR) model whose variables are aluminum futures contracts price, aluminum spot price and risk free interest rate, whereas for the aluminum spot price monthly return 27 months ahead is a single equation model in which the aluminum spot price today is explained by the aluminum futures price 27 months earlier. Finally, it shows that iterated multiperiod-ahead time series forecasts have a better conditional out-of-sample forecasting performance of the aluminum spot price monthly return when an estimated (VAR) model is used as a forecasting tool.

Bejarano Rojas, Jesus Antonio

2011-08-01T23:59:59.000Z

283

Investigating the Correlation Between Wind and Solar Power Forecast Errors in the Western Interconnection: Preprint  

DOE Green Energy (OSTI)

Wind and solar power generations differ from conventional energy generation because of the variable and uncertain nature of their power output. This variability and uncertainty can have significant impacts on grid operations. Thus, short-term forecasting of wind and solar generation is uniquely helpful for power system operations to balance supply and demand in an electricity system. This paper investigates the correlation between wind and solar power forecasting errors.

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

2013-05-01T23:59:59.000Z

284

The Skill of ECMWF Medium-Range Forecasts during the Year of Tropical Convection 2008  

Science Conference Proceedings (OSTI)

This study uses the European Centre for Medium-Range Weather Forecasts (ECMWF) model-generated high-resolution 10-day-long predictions for the Year of Tropical Convection (YOTC) 2008. Precipitation forecast skills of the model over the tropics ...

Arindam Chakraborty

2010-10-01T23:59:59.000Z

285

Object-Based Evaluation of the Impact of Horizontal Grid Spacing on Convection-Allowing Forecasts  

Science Conference Proceedings (OSTI)

Forecasts generated by the Center for Analysis and Prediction of Storms with 1- and 4-km grid spacing using the Advanced Research Weather Research and Forecasting Model (ARW-WRF; ARW1 and ARW4, respectively) for the 2009–11 NOAA Hazardous Weather ...

Aaron Johnson; Xuguang Wang; Fanyou Kong; Ming Xue

2013-10-01T23:59:59.000Z

286

The Australian Air Quality Forecasting System. Part I: Project Description and Early Outcomes  

Science Conference Proceedings (OSTI)

The Australian Air Quality Forecasting System (AAQFS) is the culmination of a 3-yr project to develop a numerical primitive equation system for generating high-resolution (1–5 km) short-term (24–36 h) forecasts for the Australian coastal cities ...

M. E. Cope; G. D. Hess; S. Lee; K. Tory; M. Azzi; J. Carras; W. Lilley; P. C. Manins; P. Nelson; L. Ng; K. Puri; N. Wong; S. Walsh; M. Young

2004-05-01T23:59:59.000Z

287

A Quick Guide to Wind Power Forecasting: State-of-the-Art 2009  

E-Print Network (OSTI)

challenges with regard to both power production and load balance in the electricity grid. This new source reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly other electricity sources, must be scheduled. Although wind power forecasting methods are used

Kemner, Ken

288

Probabilistic aspects of meteorological and ozone regional ensemble forecasts  

SciTech Connect

This study investigates whether probabilistic ozone forecasts from an ensemble can be made with skill; i.e., high verification resolution and reliability. Twenty-eight ozone forecasts were generated over the Lower Fraser Valley, British Columbia, Canada, for the 5-day period 11-15 August 2004, and compared with 1-hour averaged measurements of ozone concentrations at five stations. The forecasts were obtained by driving the CMAQ model with four meteorological forecasts and seven emission scenarios: a control run, {+-} 50% NO{sub x}, {+-} 50% VOC, and {+-} 50% NO{sub x} combined with VOC. Probabilistic forecast quality is verified using relative operating characteristic curves, Talagrand diagrams, and a new reliability index. Results show that both meteorology and emission perturbations are needed to have a skillful probabilistic forecast system--the meteorology perturbation is important to capture the ozone temporal and spatial distribution, and the emission perturbation is needed to span the range of ozone-concentration magnitudes. Emission perturbations are more important than meteorology perturbations for capturing the likelihood of high ozone concentrations. Perturbations involving NO{sub x} resulted in a more skillful probabilistic forecast for the episode analyzed, and therefore the 50% perturbation values appears to span much of the emission uncertainty for this case. All of the ensembles analyzed show a high ozone concentration bias in the Talagrand diagrams, even when the biases from the unperturbed emissions forecasts are removed from all ensemble members. This result indicates nonlinearity in the ensemble, which arises from both ozone chemistry and its interaction with input from particular meteorological models.

Monache, L D; Hacker, J; Zhou, Y; Deng, X; Stull, R

2006-03-20T23:59:59.000Z

289

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System  

SciTech Connect

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This report serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, section 57(b)(1)). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

NONE

1995-02-01T23:59:59.000Z

290

Statistical Wind Power Forecasting Models: Results for U.S. Wind Farms; Preprint  

DOE Green Energy (OSTI)

Electricity markets in the United States are evolving. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast makes it possible for grid operators to schedule the economically efficient generation to meet the demand of electrical customers. In the evolving markets, some form of auction is held for various forward markets, such as hour ahead or day ahead. This paper develops several statistical forecasting models that can be useful in hour-ahead markets that have a similar tariff. Although longer-term forecasting relies on numerical weather models, the statistical models used here focus on the short-term forecasts that can be useful in the hour-ahead markets. We investigate the extent to which time-series analysis can improve on simplistic persistence forecasts. This project applied a class of models known as autoregressive moving average (ARMA) models to both wind speed and wind power output.

Milligan, M.; Schwartz, M.; Wan, Y.

2003-05-01T23:59:59.000Z

291

Forecasting Cloud Cover and Atmospheric Seeing for Astronomical Observing: Application and Evaluation of the Global Forecast System  

E-Print Network (OSTI)

To explore the issue of performing a non-interactive numerical weather forecast with an operational global model in assist of astronomical observing, we use the Xu-Randall cloud scheme and the Trinquet-Vernin AXP seeing model with the global numerical output from the Global Forecast System to generate 3-72h forecasts for cloud coverage and atmospheric seeing, and compare them with sequence observations from 9 sites from different regions of the world with different climatic background in the period of January 2008 to December 2009. The evaluation shows that the proportion of prefect forecast of cloud cover forecast varies from ~50% to ~85%. The probability of cloud detection is estimated to be around ~30% to ~90%, while the false alarm rate is generally moderate and is much lower than the probability of detection in most cases. The seeing forecast has a moderate mean difference (absolute mean difference <0.3" in most cases) and root-mean-square-error or RMSE (0.2"-0.4" in most cases) comparing with the obs...

Ye, Q -z

2010-01-01T23:59:59.000Z

292

Assumptions to the Annual Energy Outlook - Household Expenditures Module  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module Assumption to the Annual Energy Outlook Household Expenditures Module Figure 5. United States Census Divisions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division (see

293

Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast  

E-Print Network (OSTI)

Forecast Introduction................................................................... 16 The Base Case Forecast..................................................................... 16 Base Case Price Forecast

294

Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill  

SciTech Connect

We investigated the contribution of medium range weather forecasts with lead times up to 14 days to seasonal hydrologic prediction skill over the Conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP)-based experiments were performed for the period 1980-2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980-2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts, for runoff (SM) forecasts generally varies from 0 to 0.8 (0 to 0.5) as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

Shukla, Shraddhanand; Voisin, Nathalie; Lettenmaier, D. P.

2012-08-15T23:59:59.000Z

295

Quantitative Precipitation Forecast Techniques for Use in Hydrologic Forecasting  

Science Conference Proceedings (OSTI)

Quantitative hydrologic forecasting usually requires knowledge of the spatial and temporal distribution of precipitation. First, it is important to accurately measure the precipitation falling over a particular watershed of interest. Second, ...

Konstantine P. Georgakakos; Michael D. Hudlow

1984-11-01T23:59:59.000Z

296

Transportation Sector Module 2003, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2003-02-01T23:59:59.000Z

297

Transportation Sector Module 2009, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2009-06-02T23:59:59.000Z

298

Transportation Sector Module 2006, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2006-09-01T23:59:59.000Z

299

Transportation Sector Module 2007, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2007-05-09T23:59:59.000Z

300

Transportation Sector Module 2002, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2002-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Transportation Sector Module 2001, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2001-02-01T23:59:59.000Z

302

Transportation Sector Module 2004, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2004-03-01T23:59:59.000Z

303

Transportation Sector Module 2005, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2005-06-01T23:59:59.000Z

304

Transportation Sector Module 2008, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2008-11-04T23:59:59.000Z

305

Load Forecast For use in Resource Adequacy  

E-Print Network (OSTI)

Load Forecast 2019 For use in Resource Adequacy Massoud Jourabchi #12;In today's presentation d l­ Load forecast methodology ­ Drivers of the forecast f i­ Treatment of conservation ­ Incorporating impact of weather ­ Forecast for 2019 #12;Regional Loads (MWA and MW)Regional Loads (MWA and MW

306

Forecast Technical Document Felling and Removals  

E-Print Network (OSTI)

Forecast Technical Document Felling and Removals Forecasts A document describing how volume fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Felling and removals forecasts Background A fellings and removals

307

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast. Miguel Garcia

308

Combining forecast weights: Why and how?  

Science Conference Proceedings (OSTI)

This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions

Yip Chee Yin; Ng Kok-Haur; Lim Hock-Eam

2012-01-01T23:59:59.000Z

309

PROBLEMS OF FORECAST1 Dmitry KUCHARAVY  

E-Print Network (OSTI)

1 PROBLEMS OF FORECAST1 Dmitry KUCHARAVY dmitry.kucharavy@insa-strasbourg.fr Roland DE GUIO roland for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods of the forecast errors. Second, using a contradiction analysis, a set of problems related to technology forecast

Paris-Sud XI, Université de

310

Using reforecasts for probabilistic forecast calibration  

E-Print Network (OSTI)

1 Using reforecasts for probabilistic forecast calibration Tom Hamill NOAA Earth System Research that is currently operational. #12;3 Why compute reforecasts? · For many forecast problems, such as long-lead forecasts or high-precipitation events, a few past forecasts may be insufficient for calibrating

Hamill, Tom

311

Assessing Forecast Accuracy Measures Department of Economics  

E-Print Network (OSTI)

Assessing Forecast Accuracy Measures Zhuo Chen Department of Economics Heady Hall 260 Iowa State forecast accuracy measures. In the theoretical direction, for comparing two forecasters, only when the errors are stochastically ordered, the ranking of the forecasts is basically independent of the form

312

Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model  

E-Print Network (OSTI)

1 1 Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model 2007 Federal prices are being inputted into the model 2 Sales forecast Select yearsSales forecast Select years --Draft 0.53% Irrigation 2.76% Annual Growth Rates Preliminary Electricity ForecastAnnual Growth Rates

313

Can earnings forecasts be improved by taking into account the forecast bias?  

E-Print Network (OSTI)

Can earnings forecasts be improved by taking into account the forecast bias? François DOSSOU allow the calculation of earnings adjusted forecasts, for horizons from 1 to 24 months. We explain variables. From the forecast evaluation statistics viewpoints, the adjusted forecasts make it possible quasi

Paris-Sud XI, Université de

314

Autoregressive forecast of monthly total ozone concentration: A neurocomputing approach  

Science Conference Proceedings (OSTI)

The present study endeavors to generate autoregressive neural network (AR-NN) models to forecast the monthly total ozone concentration over Kolkata (22^o34', 88^o22'), India. The issues associated with the applicability of neural network to geophysical ... Keywords: Autoregressive moving average, Autoregressive neural network, Monthly total ozone, Predictive model

Goutami Chattopadhyay; Surajit Chattopadhyay

2009-09-01T23:59:59.000Z

315

Wind Power Forecasting: State-of-the-Art 2009  

E-Print Network (OSTI)

operator (ISO) ­ Generate electricity to meet loads ­ Strive to maximize profits Independent system rules ­ Post next-day weather and load forecasts ­ Compute and post market clearing prices ­ Post unitElectric Power Market Simulations Using Individuals as Agents Guenter Conzelmann Argonne National

Kemner, Ken

316

Statistical Characteristics of a Real-Time Precipitation Forecasting Model  

Science Conference Proceedings (OSTI)

At Colorado State University the Regional Atmospheric Modeling System (RAMS) has been used to produce real-time forecasts of precipitation for the Colorado mountain region since 1991. Originally a so-called dump-bucket scheme was used to generate ...

Brian Gaudet; William R. Cotton

1998-12-01T23:59:59.000Z

317

GenForecast(26yr)(avg).PDF  

NLE Websites -- All DOE Office Websites (Extended Search)

SLCAIP Historical & Forecast Generation at Plant Total Range of Hydrology 0 2,000,000,000 4,000,000,000 6,000,000,000 8,000,000,000 10,000,000,000 12,000,000,000 1 9 7 0 1 9 7 2 1...

318

Distributed Generation Potential of the U.S. CommercialSector  

Science Conference Proceedings (OSTI)

Small-scale (100 kW-5 MW) on-site distributed generation (DG) economically driven by combined heat and power (CHP) applications and, in some cases, reliability concerns will likely emerge as a common feature of commercial building energy systems in developed countries over the next two decades. In the U.S., private and public expectations for this technology are heavily influenced by forecasts published by the Energy Information Administration (EIA), most notably the Annual Energy Outlook (AEO). EIA's forecasts are typically made using the National Energy Modeling System (NEMS), which has a forecasting module that predicts the penetration of several possible commercial building DG technologies over the period 2005-2025. Annual penetration is forecast by estimating the payback period for each technology, for each of a limited number of representative building types, for each of nine regions. This process results in an AEO2004 forecast deployment of about a total 3 GW of DG electrical generating capacity by 2025, which is only 0.25 percent of total forecast U.S. capacity. Analyses conducted using both the AEO2003 and AEO2004 versions of NEMS changes the baseline costs and performance characteristics of DG to reflect a world without U.S. Department of Energy (DOE) research into several thermal DG technologies, which is then compared to a case with enhanced technology representative of the successful achievement of DOE research goals. The net difference in 2025 DG penetration is dramatic using the AEO2003 version of NEMS, but much smaller in the AEO2004 version. The significance and validity of these contradictory results are discussed, and possibilities for improving estimates of commercial U.S. DG potential are explored.

LaCommare, Kristina Hamachi; Edwards, Jennifer L.; Gumerman,Etan; Marnay, Chris

2005-06-01T23:59:59.000Z

319

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":""}]}

320

Value of Wind Power Forecasting  

DOE Green Energy (OSTI)

This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

2011-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Fuzzy forecasting with DNA computing  

Science Conference Proceedings (OSTI)

There are many forecasting techniques including: exponential smoothing, ARIMA model, GARCH model, neural networks and genetic algorithm, etc. Since financial time series may be influenced by many factors, conventional model based techniques and hard ...

Don Jyh-Fu Jeng; Junzo Watada; Berlin Wu; Jui-Yu Wu

2006-06-01T23:59:59.000Z

322

Sampling Errors in Seasonal Forecasting  

Science Conference Proceedings (OSTI)

The limited numbers of start dates and ensemble sizes in seasonal forecasts lead to sampling errors in predictions. Defining the magnitude of these sampling errors would be useful for end users as well as informing decisions on resource ...

Stephen Cusack; Alberto Arribas

2009-03-01T23:59:59.000Z

323

Scoring Rules for Forecast Verification  

Science Conference Proceedings (OSTI)

The problem of probabilistic forecast verification is approached from a theoretical point of view starting from three basic desiderata: additivity, exclusive dependence on physical observations (“locality”), and strictly proper behavior. By ...

Riccardo Benedetti

2010-01-01T23:59:59.000Z

324

Wavelets and Field Forecast Verification  

Science Conference Proceedings (OSTI)

Current field forecast verification measures are inadequate, primarily because they compress the comparison between two complex spatial field processes into one number. Discrete wavelet transforms (DWTs) applied to analysis and contemporaneous ...

William M. Briggs; Richard A. Levine

1997-06-01T23:59:59.000Z

325

Richardson's Barotropic Forecast: A Reappraisal  

Science Conference Proceedings (OSTI)

To elucidate his numerical technique and to examine the effectiveness of geostrophic initial winds, Lewis Fry Richardson carried out an idealized forecast using the linear shallow-water equations and simple analytical pressure and velocity ...

Peter Lynch

1992-01-01T23:59:59.000Z

326

Downscaling Extended Weather Forecasts for Hydrologic Prediction  

SciTech Connect

Weather and climate forecasts are critical inputs to hydrologic forecasting systems. The National Center for Environmental Prediction (NCEP) issues 8-15 days outlook daily for the U.S. based on the Medium Range Forecast (MRF) model, which is a global model applied at about 2? spatial resolution. Because of the relatively coarse spatial resolution, weather forecasts produced by the MRF model cannot be applied directly to hydrologic forecasting models that require high spatial resolution to represent land surface hydrology. A mesoscale atmospheric model was used to dynamically downscale the 1-8 day extended global weather forecasts to test the feasibility of hydrologic forecasting through this model nesting approach. Atmospheric conditions of each 8-day forecast during the period 1990-2000 were used to provide initial and boundary conditions for the mesoscale model to produce an 8-day atmospheric forecast for the western U.S. at 30 km spatial resolution. To examine the impact of initialization of the land surface state on forecast skill, two sets of simulations were performed with the land surface state initialized based on the global forecasts versus land surface conditions from a continuous mesoscale simulation driven by the NCEP reanalysis. Comparison of the skill of the global and downscaled precipitation forecasts in the western U.S. showed higher skill for the downscaled forecasts at all precipitation thresholds and increasingly larger differences at the larger thresholds. Analyses of the surface temperature forecasts show that the mesoscale forecasts generally reduced the root-mean-square error by about 1.5 C compared to the global forecasts, because of the much better resolved topography at 30 km spatial resolution. In addition, initialization of the land surface states has large impacts on the temperature forecasts, but not the precipitation forecasts. The improvements in forecast skill using downscaling could be potentially significant for improving hydrologic forecasts for managing river basins.

Leung, Lai-Yung R.; Qian, Yun

2005-03-01T23:59:59.000Z

327

Framing Scenarios of Electricity Generation and Gas Use: EPRI Report Series on Gas Demands for Power Generation  

Science Conference Proceedings (OSTI)

This report provides a systematic appraisal of trends in electric generation and demands for gas for power generation. Gas-fired generation is the leading driver of forecasted growth in demand for natural gas in the United States, and natural gas is a leading fuel for planned new generating capacity. The report goes behind the numbers and forecasts to quantify key drivers and uncertainties.

1996-08-28T23:59:59.000Z

328

Light truck forecasts  

SciTech Connect

The recent dramatic increase in the number of light trucks (109% between 1963 and 1974) has prompted concern about the energy consequences of the growing popularity of the light truck. An estimate of the future number of light trucks is considered to be a reasonable first step in assessing the energy impact of these vehicles. The monograph contains forecasts based on two models and six scenarios. The coefficients for the models have been derived by ordinary least squares regression of national level time series data. The first model is a two stage model. The first stage estimates the number of light trucks and cars (together), and the second stage applies a share's submodel to determine the number of light trucks. The second model is a simultaneous equation model. The two models track one another remarkably well, within about 2%. The scenarios were chosen to be consistent with those used in the Lindsey-Kaufman study Projection of Light Truck Population to Year 2025. Except in the case of the most dismal economic scenario, the number of light trucks is expected to increase from the 1974 level of 0.09 light truck per person to about 0.12 light truck per person in 1995.

Liepins, G.E.

1979-09-01T23:59:59.000Z

329

Impact of ECCO Ocean-State Estimates on the Initialization of Seasonal Climate Forecasts  

Science Conference Proceedings (OSTI)

The impact of ocean-state estimates generated by the consortium for Estimating the Circulation and Climate of the Ocean (ECCO) on the initialization of a coupled general circulation model (CGCM) for seasonal climate forecasts is examined. The ...

Gabriel Cazes-Boezio; Dimitris Menemenlis; Carlos R. Mechoso

2008-05-01T23:59:59.000Z

330

Calibrating Multimodel Forecast Ensembles with Exchangeable and Missing Members Using Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Bayesian model averaging (BMA) is a statistical postprocessing technique that generates calibrated and sharp predictive probability density functions (PDFs) from forecast ensembles. It represents the predictive PDF as a weighted average of PDFs ...

Chris Fraley; Adrian E. Raftery; Tilmann Gneiting

2010-01-01T23:59:59.000Z

331

Short-Range Ensemble Forecasts of Precipitation during the Southwest Monsoon  

Science Conference Proceedings (OSTI)

The skill and potential value of fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) ensembles are evaluated for short-range (24 h) probabilistic quantitative precipitation forecasts over ...

David R. Bright; Steven L. Mullen

2002-10-01T23:59:59.000Z

332

Multiresolution Ensemble Forecasts of an Observed Tornadic Thunderstorm System. Part II: Storm-Scale Experiments  

Science Conference Proceedings (OSTI)

In Part I, the authors used a full physics, nonhydrostatic numerical model with horizontal grid spacing of 24 km and nested grids of 6- and 3-km spacing to generate the ensemble forecasts of an observed tornadic thunderstorm complex. The ...

Fanyou Kong; Kelvin K. Droegemeier; Nicki L. Hickmon

2007-03-01T23:59:59.000Z

333

An Analysis of NCEP Tropical Cyclone Vitals and Potential Effects on Forecasting Models  

Science Conference Proceedings (OSTI)

This study analyzes the Tropical Cyclone Vitals Database (TCVitals), which contains cyclone location, intensity, and structure information, generated in real time by forecasters. These data are used to initialize cyclones in several NCEP ...

Sam Trahan; Lynn Sparling

2012-06-01T23:59:59.000Z

334

Anthropogenic Moisture Effects on WRF Summertime Surface Temperature and Mixing Ratio Forecast Skill In Southern California  

Science Conference Proceedings (OSTI)

Mesoscale forecasts for the Los Angeles basin made with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) exhibited a moderate to substantial warm temperature bias for extended ...

Rich F. Coleman; James F. Drake; Michael D. McAtee; Leslie O. Belsma

2010-10-01T23:59:59.000Z

335

The Land Surface Analysis in the NCEP Climate Forecast System Reanalysis  

Science Conference Proceedings (OSTI)

The NCEP Climate Forecast System Reanalysis (CFSR) uses the NASA Land Information System (LIS) to create its land surface analysis: the NCEP Global Land Data Assimilation System (GLDAS). Comparing to the previous two generations of NCEP global ...

Jesse Meng; Rongqian Yang; Helin Wei; Michael Ek; George Gayno; Pingping Xie; Kenneth Mitchell

2012-10-01T23:59:59.000Z

336

Extending the Limits of Ensemble Forecast Verification with the Minimum Spanning Tree  

Science Conference Proceedings (OSTI)

Uncertainty in the initial condition is one of the factors that limits the utility of single-model-run predictions of even deterministic nonlinear systems. In practice, an ensemble of initial conditions is often used to generate forecasts with ...

Leonard A. Smith; James A. Hansen

2004-06-01T23:59:59.000Z

337

Will Perturbing Soil Moisture Improve Warm-Season Ensemble Forecasts? A Proof of Concept  

Science Conference Proceedings (OSTI)

Current generation short-range ensemble forecast members tend to be unduly similar to each other, especially for components such as surface temperature and precipitation. One possible cause of this is a lack of perturbations to the land surface ...

Christian Sutton; Thomas M. Hamill; Thomas T. Warner

2006-11-01T23:59:59.000Z

338

Comparison of AEO 2005 natural gas price forecast to NYMEX futures prices  

E-Print Network (OSTI)

to the EIA’s natural gas price forecasts in AEO 2004 and AEOcost comparisons of fixed-price renewable generationwith variable price gas-fired generation that are based

Bolinger, Mark; Wiser, Ryan

2004-01-01T23:59:59.000Z

339

WSRC Nuclear Materials Cost Module  

National Nuclear Security Administration (NNSA)

Office (GAO) WSRC NM Cost Module Generates WSRC monthly and fiscal year to date Inventory and Manufacturing Statement for government owned accountable nuclear materials....

340

Conceptual design of a geothermal site development forecasting system  

DOE Green Energy (OSTI)

A site development forecasting system has been designed in response to the need to monitor and forecast the development of specific geothermal resource sites for electrical power generation and direct heat applications. The system is comprised of customized software, a site development status data base, and a set of complex geothermal project development schedules. The system would use site-specific development status information obtained from the Geothermal Progress Monitor and other data derived from economic and market penetration studies to produce reports on the rates of geothermal energy development, federal agency manpower requirements to ensure these developments, and capital expenditures and technical/laborer manpower required to achieve these developments.

Neham, E.A.; Entingh, D.J.

1980-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

The Potential Impact of Using Persistence as a Reference Forecast on Perceived Forecast Skill  

Science Conference Proceedings (OSTI)

Skill is defined as actual forecast performance relative to the performance of a reference forecast. It is shown that the choice of reference (e.g., random or persistence) can affect the perceived performance of the forecast system. Two scores, ...

Marion P. Mittermaier

2008-10-01T23:59:59.000Z

342

The Complex Relationship between Forecast Skill and Forecast Value: A Real-World Analysis  

Science Conference Proceedings (OSTI)

For routine forecasts of temperature and precipitation, the relative skill advantage of human forecasters with respect to the numerical–statistical guidance is small (and diminishing). Since the relationship between forecast skill and the value ...

Paul J. Roebber; Lance F. Bosart

1996-12-01T23:59:59.000Z

343

Quantification of Uncertainity in Fire-Weather Forecasts: Some Results of Operational and Experimental Forecasting Programs  

Science Conference Proceedings (OSTI)

Fire-weather forecasts (FWFs) prepared by National Weather Service (NWS) forecasters on an operational basis are traditionally expressed in categorical terms. However, to make rational and optimal use of such forecasts, fire managers need ...

Barbara G. Brown; Allan H. Murphy

1987-09-01T23:59:59.000Z

344

Ability to Forecast Regional Soil Moisture with a Distributed Hydrological Model Using ECMWF Rainfall Forecasts  

Science Conference Proceedings (OSTI)

This study mimics an online forecast system to provide nine day-ahead forecasts of regional soil moisture. It uses modified ensemble rainfall forecasts from the numerical weather prediction model of the European Centre for Medium-Range Weather ...

J. M. Schuurmans; M. F. P. Bierkens

2009-04-01T23:59:59.000Z

345

Spatial Structure, Forecast Errors, and Predictability of the South Asian Monsoon in CFS Monthly Retrospective Forecasts  

Science Conference Proceedings (OSTI)

The spatial structure of the boreal summer South Asian monsoon in the ensemble mean of monthly retrospective forecasts by the Climate Forecast System of the National Centers for Environmental Prediction is examined. The forecast errors and ...

Hae-Kyung Lee Drbohlav; V. Krishnamurthy

2010-09-01T23:59:59.000Z

346

What Is a Good Forecast? An Essay on the Nature of Goodness in Weather Forecasting  

Science Conference Proceedings (OSTI)

Differences of opinion exist among forecasters—and between forecasters and users—regarding the meaning of the phrase “good (bad) weather forecasts.” These differences of opinion are fueled by a lack of clarity and/or understanding concerning the ...

Allan H. Murphy

1993-06-01T23:59:59.000Z

347

Statistical Wind Power Forecasting for U.S. Wind Farms: Preprint  

DOE Green Energy (OSTI)

Electricity markets in the United States are evolving. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. The evolving markets hold some form of auction for various forward markets, such as hour ahead or day ahead. This paper describes several statistical forecasting models that can be useful in hour-ahead markets. Although longer-term forecasting relies on numerical weather models, the statistical models used here focus on the short-term forecasts that can be useful in the hour-ahead markets. The purpose of the paper is not to develop forecasting models that can compete with commercially available models. Instead, we investigate the extent to which time-series analysis can improve simplistic persistence forecasts. This project applied a class of models known as autoregressive moving average (A RMA) models to both wind speed and wind power output. The results from wind farms in Minnesota, Iowa, and along the Washington-Oregon border indicate that statistical modeling can provide a significant improvement in wind forecasts compared to persistence forecasts.

Milligan, M.; Schwartz, M. N.; Wan, Y.

2003-11-01T23:59:59.000Z

348

A Model of U.S. Commercial Distributed Generation Adoption  

Science Conference Proceedings (OSTI)

Small-scale (100 kW-5 MW) on-site distributed generation (DG) economically driven by combined heat and power (CHP) applications and, in some cases, reliability concerns will likely emerge as a common feature of commercial building energy systems over the next two decades. Forecasts of DG adoption published by the Energy Information Administration (EIA) in the Annual Energy Outlook (AEO) are made using the National Energy Modeling System (NEMS), which has a forecasting module that predicts the penetration of several possible commercial building DG technologies over the period 2005-2025. NEMS is also used for estimating the future benefits of Department of Energy research and development used in support of budget requests and management decisionmaking. The NEMS approach to modeling DG has some limitations, including constraints on the amount of DG allowed for retrofits to existing buildings and a small number of possible sizes for each DG technology. An alternative approach called Commercial Sector Model (ComSeM) is developed to improve the way in which DG adoption is modeled. The approach incorporates load shapes for specific end uses in specific building types in specific regions, e.g., cooling in hospitals in Atlanta or space heating in Chicago offices. The Distributed Energy Resources Customer Adoption Model (DER-CAM) uses these load profiles together with input cost and performance DG technology assumptions to model the potential DG adoption for four selected cities and two sizes of five building types in selected forecast years to 2022. The Distributed Energy Resources Market Diffusion Model (DER-MaDiM) is then used to then tailor the DER-CAM results to adoption projections for the entire U.S. commercial sector for all forecast years from 2007-2025. This process is conducted such that the structure of results are consistent with the structure of NEMS, and can be re-injected into NEMS that can then be used to integrate adoption results into a full forecast.

LaCommare, Kristina Hamachi; Ryan Firestone; Zhou, Nan; Maribu,Karl; Marnay, Chris

2006-01-10T23:59:59.000Z

349

California Regional Wind Energy Forecasting System Development, Vol. 3  

Science Conference Proceedings (OSTI)

The rated capacity of wind generation in California is expected to grow rapidly in the future beyond the approximately 2100 MW in place at the end of 2005. The main drivers are the state's 20 percent Renewable Portfolio Standard requirement in 2010 and the low cost of wind energy relative to other renewable energy sources. As wind is an intermittent generation resource and weather changes can cause large and rapid changes in output, system operators will need accurate and robust wind energy forecasting ...

2006-11-15T23:59:59.000Z

350

Base Resource Forecasts - Power Marketing - Sierra Nevada Region...  

NLE Websites -- All DOE Office Websites (Extended Search)

Marketing > Base Resource Forecasts Base Resource Forecasts Note: Annual, rolling (monthly for 12 months), base resource forecasts are posted when they become available. Annual...

351

Forecasting new product penetration with flexible substitution patterns  

E-Print Network (OSTI)

choice model for forecasting demand for alternative-fuel7511, Urban Travel Demand Forecasting Project, Institute of89 (1999) 109—129 Forecasting new product penetration with ?

Brownstone, David; Train, Kenneth

1999-01-01T23:59:59.000Z

352

Overestimation Reduction in Forecasting Telecommuting as a TDM Policy  

E-Print Network (OSTI)

M. , Ethics and advocacy in forecasting for public policy.change and social forecasting: the case of telecommuting asOverestimation Reduction in Forecasting Telecommuting as a

Tal, Gil

2008-01-01T23:59:59.000Z

353

Forecasting US CO2 Emissions Using State-Level Data  

E-Print Network (OSTI)

F. Hendry (eds), Economic Forecasting, Blackwell Publishing,W. : 2002, Macroeconomic forecasting using di?usion indexes,2003, Macroeconomic forecasting in the euro area: Country

Steinhauser, Ralf; Auffhammer, Maximilian

2005-01-01T23:59:59.000Z

354

NoVaS Transformations: Flexible Inference for Volatility Forecasting  

E-Print Network (OSTI)

and Correlation Forecasting” in G. Elliott, C.W.J.Handbook of Economic Forecasting, Amsterdam: North-Holland,Transformations”, forthcoming in Forecasting in the Presence

Politis, Dimitris N; Thomakos, Dimitrios D

2008-01-01T23:59:59.000Z

355

Forecasting new product penetration with flexible substitution patterns  

E-Print Network (OSTI)

7511, Urban Travel Demand Forecasting Project, Institute ofchoice model for forecasting demand for alternative-fuel89 (1999) 109—129 Forecasting new product penetration with

Brownstone, David; Train, Kenneth

1999-01-01T23:59:59.000Z

356

Earthquake Forecasting in Diverse Tectonic Zones of the Globe  

E-Print Network (OSTI)

Long-term probabilistic forecasting of earthquakes, J.2000), Probabilistic forecasting of earthquakes, Geophys. J.F.F. (2006), The EEPAS forecasting model and the probability

Kagan, Y. Y.; Jackson, D. D.

2010-01-01T23:59:59.000Z

357

Ensemble-based methods for forecasting census in hospital units  

E-Print Network (OSTI)

P, Fitzgerald G: Regression forecasting of patient admissionapproach to modeling and forecasting demand in the emergencySJ, Haug PJ, Snow GL: Forecasting daily patient volumes in

Koestler, Devin C; Ombao, Hernando; Bender, Jesse

2013-01-01T23:59:59.000Z

358

Forecasting Danerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures  

E-Print Network (OSTI)

costs could alter forecasting skill and the predictors thatForecasting Dangerous Inmate Misconduct: An Applications ofOn-Line Working Paper Series Forecasting Dangerous Inmate

Berk, Richard A.; Kriegler, Brian; Baek, John-Ho

2005-01-01T23:59:59.000Z

359

Developing a Practical Forecasting Screener for Domestic Violence Incidents  

E-Print Network (OSTI)

Developing a Practical Forecasting Screener for Domesticcomplicated did not improve forecasting skill. Taking thethe local costs of forecasting errors. It is also feasible

Richard A. Berk; Susan B. Sorenson; Yan He

2011-01-01T23:59:59.000Z

360

Forecasting with Dynamic Microsimulation: Design, Implementation, and Demonstration  

E-Print Network (OSTI)

Goulias Page 84 Forecasting with Dynamic Microsimulation:Goulias Page 80 Forecasting with Dynamic Microsimulation:L. Demographic Forecasting with a Dynamic Stochastic

Ravulaparthy, Srinath; Goulias, Konstadinos G.

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Annual Energy Outlook Forecast Evaluation-Table 1  

Annual Energy Outlook 2012 (EIA)

Annual Energy Outlook Forecast Evaluation > Table 1 Annual Energy Outlook Forecast Evaluation Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to...

362

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007 INTEGRATED Table of Contents General Instructions for Demand Forecast Submittals.............................................................................. 4 Protocols for Submitted Demand Forecasts

363

Roots of Ensemble Forecasting  

Science Conference Proceedings (OSTI)

The generation of a probabilistic view of dynamical weather prediction is traced back to the early 1950s, to that point in time when deterministic short-range numerical weather prediction (NWP) achieved its earliest success. Eric Eady was the ...

John M. Lewis

2005-07-01T23:59:59.000Z

364

Electricity Market Module  

U.S. Energy Information Administration (EIA) Indexed Site

Market Module Market Module This page inTenTionally lefT blank 101 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2013, DOE/EIA-M068(2013). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

365

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"

366

PDSF Modules  

NLE Websites -- All DOE Office Websites (Extended Search)

Modules Modules Modules Modules Approach to Managing The Environment Modules is a system which you can use to specify what software you want to use. If you want to use a particular software package loading its module will take care of the details of modifying your environment as necessary. The advantage of the modules approach is that the you are not required to explicitly specify paths for different executable versions and try to keep their related man paths and environment variables coordinated. Instead you simply "load" and "unload" specific modules to control your environment. Getting Started with Modules If you're using the standard startup files on PDSF then you're already setup for using modules. If the "module" command is not available, please

367

Method of monolithic module assembly  

DOE Patents (OSTI)

Methods for "monolithic module assembly" which translate many of the advantages of monolithic module construction of thin-film PV modules to wafered c-Si PV modules. Methods employ using back-contact solar cells positioned atop electrically conductive circuit elements affixed to a planar support so that a circuit capable of generating electric power is created. The modules are encapsulated using encapsulant materials such as EVA which are commonly used in photovoltaic module manufacture. The methods of the invention allow multiple cells to be electrically connected in a single encapsulation step rather than by sequential soldering which characterizes the currently used commercial practices.

Gee, James M. (Albuquerque, NM); Garrett, Stephen E. (Albuquerque, NM); Morgan, William P. (Albuquerque, NM); Worobey, Walter (Albuquerque, NM)

1999-01-01T23:59:59.000Z

368

Annual Energy Outlook 2001-Appendix G: Major Assumptions for the Forecasts  

Gasoline and Diesel Fuel Update (EIA)

Forecasts Forecasts Summary of the AEO2001 Cases/ Scenarios - Appendix Table G1 bullet1.gif (843 bytes) Model Results (Formats - PDF, ZIP) - Appendix Tables - Reference Case - 1998 to 2020 bullet1.gif (843 bytes) Download Report - Entire AEO2001 (PDF) - AEO2001 by Chapters (PDF) bullet1.gif (843 bytes) Acronyms bullet1.gif (843 bytes) Contacts Related Links bullet1.gif (843 bytes) Assumptions to the AEO2001 bullet1.gif (843 bytes) Supplemental Data to the AEO2001 (Only available on the Web) - Regional and more detailed AEO 2001 Reference Case Results - 1998, 2000 to 2020 bullet1.gif (843 bytes) NEMS Conference bullet1.gif (843 bytes) Forecast Homepage bullet1.gif (843 bytes) EIA Homepage Appendix G Major Assumptions for the Forecasts Component Modules Major Assumptions for the Annual Energy Outlook 2001

369

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

370

IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 19, NO. 1, MARCH 2004 151 Production Cost Analysis of Dispersed Generation  

E-Print Network (OSTI)

) resources to meet forecasted load growth, particularly the application of photovoltaic (PV) generation. II, called area , has self-sufficiency in generation capacity to meet its current and forecasted load for area to meet its forecasted load effectively. This re- quires the installation of additional generation

Gross, George

371

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

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

372

The Impact of Wind Power Generation on Wholesale Electricity Price ...  

Science Conference Proceedings (OSTI)

price for power generation are examined to forecast LNG price for power genera- tion. Information on future power plant's construction and decommission plan ...

373

A Review of Numerical Forecast Guidance for Hurricane Hugo  

Science Conference Proceedings (OSTI)

Numerical forecast guidance for Hurricane Hugo from the National Meteorological Center is examined, as well as forecasts from the European Center for Medium Range Forecasting and the United Kingdom Meteorological Office. No one forecast product ...

John H. Ward

1990-09-01T23:59:59.000Z

374

Short-Range Ensemble Forecasts of Precipitation Type  

Science Conference Proceedings (OSTI)

Short-range ensemble forecasting is extended to a critical winter weather problem: forecasting precipitation type. Forecast soundings from the operational NCEP Short-Range Ensemble Forecast system are combined with five precipitation-type ...

Matthew S. Wandishin; Michael E. Baldwin; Steven L. Mullen; John V. Cortinas Jr.

2005-08-01T23:59:59.000Z

375

Summary Verification Measures and Their Interpretation for Ensemble Forecasts  

Science Conference Proceedings (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

376

Using Customers' Reported Forecasts to Predict Future Sales  

E-Print Network (OSTI)

Using Customers' Reported Forecasts to Predict Future Sales Nihat Altintas , Alan Montgomery orders using forecasts provided by their customers. Our goal is to improve the supplier's operations through a better un- derstanding of the customers's forecast behavior. Unfortunately, customer forecasts

Murphy, Robert F.

377

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

DOE Green Energy (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

378

The Automated Tropical Cyclone Forecasting System (ATCF)  

Science Conference Proceedings (OSTI)

The U.S. Navy Automated Tropical Cyclone Forecasting System (ATCF) is an IBM-AT compatible software package developed for the Joint Typhoon Warning Center (JTWC), Guam. ATCF is designed to assist forecasters with the process of making tropical ...

Ronald J. Miller; Ann J. Schrader; Charles R. Sampson; Ted L. Tsui

1990-12-01T23:59:59.000Z

379

Evaluation of LFM-2 Quantitative Precipitation Forecasts  

Science Conference Proceedings (OSTI)

The results of a near real time experiment designed to assess the state of the art of quantitative precipitation forecasting skill of the operational NMC LFM-2 are described. All available LFM-2 quantitative precipitation forecasts were verified ...

Lance F. Bosart

1980-08-01T23:59:59.000Z

380

Forecaster Workstation Design: Concepts and Issues  

Science Conference Proceedings (OSTI)

Some basic ideas about designing a meteorological workstation for operational weather forecasting are presented, in part as a complement to the recently published discussion of workstation design by R. R. Hoffman. Scientific weather forecasting ...

Charles A. Doswell III

1992-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Performance of Recent Multimodel ENSO Forecasts  

Science Conference Proceedings (OSTI)

The performance of the International Research Institute for Climate and Society “ENSO forecast plume” during the 2002–11 period is evaluated using deterministic and probabilistic verification measures. The plume includes multiple model forecasts ...

Michael K. Tippett; Anthony G. Barnston; Shuhua Li

2012-03-01T23:59:59.000Z

382

Local Forecast Communication In The Altiplano  

Science Conference Proceedings (OSTI)

Forecasts play an important role in planting decisions for Andean peasant producers. Predictions of the upcoming cropping season determine when, where, and what farmers will plant. This research looks at the sources of forecast information used ...

Jere L. Gilles; Corinne Valdivia

2009-01-01T23:59:59.000Z

383

Bayesian Model Verification of NWP Ensemble Forecasts  

Science Conference Proceedings (OSTI)

Forecasts of convective precipitation have large uncertainties. To consider the forecast uncertainties of convection-permitting models, a convection-permitting ensemble prediction system (EPS) based on the Consortium for Small-scale Modeling (...

Andreas Röpnack; Andreas Hense; Christoph Gebhardt; Detlev Majewski

2013-01-01T23:59:59.000Z

384

Economic and Statistical Measures of Forecast Accuracy  

E-Print Network (OSTI)

This paper argues in favour of a closer link between decision and forecast evaluation problems. Although the idea of using decision theory for forecast evaluation appears early in the dynamic stochastic programming literature, and has continued...

Granger, Clive W J; Pesaran, M Hashem

2004-06-16T23:59:59.000Z

385

2013 Midyear Economic Forecast Sponsorship Opportunity  

E-Print Network (OSTI)

2013 Midyear Economic Forecast Sponsorship Opportunity Thursday, April 18, 2013, ­ Hyatt Regency Irvine 11:30 a.m. ­ 1:30 p.m. Dr. Anil Puri presents his annual Midyear Economic Forecast addressing

de Lijser, Peter

386

Forecasting consumer products using prediction markets  

E-Print Network (OSTI)

Prediction Markets hold the promise of improving the forecasting process. Research has shown that Prediction Markets can develop more accurate forecasts than polls or experts. Our research concentrated on analyzing Prediction ...

Trepte, Kai

2009-01-01T23:59:59.000Z

387

Intercomparison of Spatial Forecast Verification Methods  

Science Conference Proceedings (OSTI)

Advancements in weather forecast models and their enhanced resolution have led to substantially improved and more realistic-appearing forecasts for some variables. However, traditional verification scores often indicate poor performance because ...

Eric Gilleland; David Ahijevych; Barbara G. Brown; Barbara Casati; Elizabeth E. Ebert

2009-10-01T23:59:59.000Z

388

Forecasting with Reference to a Specific Climatology  

Science Conference Proceedings (OSTI)

Seasonal forecasts are most commonly issued as anomalies with respect to some multiyear reference period. However, different seasonal forecasting centers use different reference periods. This paper shows that for near-surface temperature, ...

Emily Wallace; Alberto Arribas

2012-11-01T23:59:59.000Z

389

Probabilistic Quantitative Precipitation Forecasts for River Basins  

Science Conference Proceedings (OSTI)

A methodology has been formulated to aid a field forecaster in preparing probabilistic quantitative precipitation forecasts (QPFs) for river basins. The format of probabilistic QPF is designed to meet three requirements: (i) it is compatible with ...

Roman Krzysztofowicz; William J. Drzal; Theresa Rossi Drake; James C. Weyman; Louis A. Giordano

1993-12-01T23:59:59.000Z

390

A General Framework for Forecast Verification  

Science Conference Proceedings (OSTI)

A general framework for forecast verification based on the joint distribution of forecasts and observations is described. For further elaboration of the framework, two factorizations of the joint distribution are investigated: 1) the calibration-...

Allan H. Murphy; Robert L. Winkler

1987-07-01T23:59:59.000Z

391

Antarctic Satellite Meteorology: Applications for Weather Forecasting  

Science Conference Proceedings (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

392

Value from Ambiguity in Ensemble Forecasts  

Science Conference Proceedings (OSTI)

This study explores the objective application of ambiguity information, that is, the uncertainty in forecast probability derived from an ensemble. One application approach, called uncertainty folding, merges ambiguity with forecast uncertainty ...

Mark S. Allen; F. Anthony Eckel

2012-02-01T23:59:59.000Z

393

NEMS industrial module documentation report  

SciTech Connect

The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2010) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of output of industrial activity. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

1994-01-01T23:59:59.000Z

394

Voluntary Green Power Market Forecast through 2015  

SciTech Connect

Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

2010-05-01T23:59:59.000Z

395

Voluntary Green Power Market Forecast through 2015  

SciTech Connect

Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

2010-05-01T23:59:59.000Z

396

Management of supply chain: an alternative modelling technique for forecasting  

E-Print Network (OSTI)

Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view

Datta, Shoumen

2007-05-23T23:59:59.000Z

397

Improving week two forecasts with multi-model re-forecast ensembles  

E-Print Network (OSTI)

Improving week two forecasts with multi-model re-forecast ensembles Jeffrey S. Whitaker and Xue Wei NOAA-CIRES Climate Diagnostics Center, Boulder, CO Fr´ed´eric Vitart Seasonal Forecasting Group, ECMWF dataset of ensemble 're-forecasts' from a single model can significantly improve the skill

Whitaker, Jeffrey S.

398

Forecasting for energy and chemical decision analysis  

SciTech Connect

This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.

Cazalet, E.G.

1984-08-01T23:59:59.000Z

399

A Rank Approach to Equity Forecast Construction  

E-Print Network (OSTI)

that are fit for their purpose; for example, returningaggregate county and sector forecasts that are consistent by construction....

Satchell, Stephen E; Wright, Stephen M

2006-03-14T23:59:59.000Z

400

Forecasting Techniques Utilized by the Forecast Branch of the National Meteorological Center During a Major Convective Rainfall Event  

Science Conference Proceedings (OSTI)

Meteorologists within the Forecast Branch (FB) of the National Meteorological Center (NMC) produce operational quantitative precipitation forecasts (QPFs). These manual forecasts are prepared utilizing various forecasting techniques, which are ...

Theodore W. Funk

1991-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Application of Forecast Verification Science to Operational River Forecasting in the U.S. National Weather Service  

Science Conference Proceedings (OSTI)

Forecast verification in operational hydrology has been very limited to date, mainly due to the complexity of verifying both forcing input forecasts and hydrologic forecasts on multiple space–time scales. However, forecast verification needs to ...

Julie Demargne; Mary Mullusky; Kevin Werner; Thomas Adams; Scott Lindsey; Noreen Schwein; William Marosi; Edwin Welles

2009-06-01T23:59:59.000Z

402

Load Forecasting for Modern Distribution Systems  

Science Conference Proceedings (OSTI)

Load forecasting is a fundamental activity for numerous organizations and activities within a utility, including planning, operations, and control. Transmission and Distribution (T&D) planning and design engineers use the load forecast to determine whether any changes and additions are needed to the electric system to satisfy the anticipated load. Other load forecast users include system operations, financial ...

2013-03-08T23:59:59.000Z

403

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

404

Modeling and Forecasting Electric Daily Peak Loads  

E-Print Network (OSTI)

Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity 29, 2012 Preliminary Results of the Electricity Price Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity market price forecast. A summary of the work

Abdel-Aal, Radwan E.

405

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

406

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

407

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

408

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

409

Load forecast and treatment of conservation  

E-Print Network (OSTI)

Load forecast and treatment of conservation July 28th 2010 Resource Adequacy Technical Committee conservation is implicitly incorporated in the short-term demand forecast? #12;3 Incorporating conservation in the short-term model Our short-term model is an econometric model which can not explicitly forecast

410

FINAL STAFF FORECAST OF 2008 PEAK DEMAND  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

411

STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 report, Staff Forecast: Retail Electricity Prices, 2005 to 2018, was prepared with contributions from the technical assistance provided by Greg Broeking of R.W. Beck, Inc. in preparing retail price forecasts

412

Blue Chip Consensus US GDP Forecast  

E-Print Network (OSTI)

and metro area from Moody’s Economy.com Equivalent to US-level Gross Domestic Product ? The GMP forecasts have a large impact on the peak load forecasts Rule of thumb: 1 % growth in RTO GMP ? approx. 1,000 MW growth in forecast RTO peak load

James F. Wilson

2007-01-01T23:59:59.000Z

413

5, 183218, 2008 A rainfall forecast  

E-Print Network (OSTI)

HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N. Q. Hung et al An artificial neural network model for rainfall forecasting in Bangkok, Thailand N. Q. Hung, M. S. Babel, S Geosciences Union. 183 #12;HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N

Paris-Sud XI, Université de

414

(1) Ensemble forecast calibration & (2) using reforecasts  

E-Print Network (OSTI)

1 (1) Ensemble forecast calibration & (2) using reforecasts Tom Hamill NOAA Earth System Research · Calibration: ; the statistical adjustment of the (ensemble) forecast ­ Rationale 1: Infer large-sample probabilities from small ensemble. ­ Rationale 2: Remove bias, increase forecast reliability while preserving

Hamill, Tom

415

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

416

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 of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach can forecast the price of a notebook computer up to four months in advance of its introduction with an average error of under 10% and the rate of price erosion to within 10% of the price for seven months after introduction-the length of the typical life cycle of a notebook. Since all data are publicly available, this approach can be used to assist managerial decision making in the notebook computer industry, for example, in determining when and how to upgrade a model and when to introduce a new model.

Rutherford, Derek Paul

1997-01-01T23:59:59.000Z

417

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.

418

How Do You Like Your Weather?: Using Weather Forecast Data to Improve Short-Term Load Forecasts  

Science Conference Proceedings (OSTI)

This document provides a quick overview of weather forecasts as a data issue in the development of electricity demand forecasts. These are three sections in this Brief: o reasons behind the rise in interest in using weather forecasts in electricity forecasting models, o an overview of what some utilities are doing to evaluate weather forecasts, and o a resource list of weather forecast providers.

2001-09-28T23:59:59.000Z

419

On-line economic optimization of energy systems using weather forecast information.  

Science Conference Proceedings (OSTI)

We establish an on-line optimization framework to exploit weather forecast information in the operation of energy systems. We argue that anticipating the weather conditions can lead to more proactive and cost-effective operations. The framework is based on the solution of a stochastic dynamic real-time optimization (D-RTO) problem incorporating forecasts generated from a state-of-the-art weather prediction model. The necessary uncertainty information is extracted from the weather model using an ensemble approach. The accuracy of the forecast trends and uncertainty bounds are validated using real meteorological data. We present a numerical simulation study in a building system to demonstrate the developments.

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

2009-01-01T23:59:59.000Z

420

Electricity Market Module  

Reports and Publications (EIA)

Documents the Electricity Market Module as it was used for the Annual Energy Outlook 2013. The Electricity Market Module (EMM) is the electricity supply component of the National Energy Modeling System (NEMS). The EMM represents the generation, transmission, and pricing of electricity. It consists of four submodules: the Electricity Capacity Planning (ECP) Submodule, the Electricity Fuel Dispatch (EFD) Submodule, the Electricity Finance and Pricing (EFP) Submodule, and the Electricity Load and Demand (ELD) Submodule.

Jeff Jones

2013-07-24T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA

422

EIA-Assumptions to the Annual Energy Outlook - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2007 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind.112 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost energy storage systems.

423

Weather forecast-based optimization of integrated energy systems.  

SciTech Connect

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

424

Critical Operating Constraint Forecasting (COCF)  

Science Conference Proceedings (OSTI)

This document represents the progress report and Task 1 letter report of the California Institute for Energy and Environment (CIEE) contract funded by the California Energy Commission (CEC), Critical Operating Constraint Forecasting (COCF) for California Independent System Operator (CAISO) Planning Phase. Task 1 was to accomplish the following items: Collect data from CAISO to set up the WECC power flow base case representing the CAISO system in the summer of 2006 Run TRACE for maximizing California Impo...

2006-06-30T23:59:59.000Z

425

Performance of Observation-Based Prediction Algorithms for Very Short-Range, Probabilistic Clear-Sky Condition Forecasting  

Science Conference Proceedings (OSTI)

Very short-range sky condition forecasts are produced to support a variety of military, civil, and commercial activities. In this investigation, six advanced, observation (obs)-based prediction algorithms were developed and tested that generated ...

Timothy J. Hall; Carl N. Mutchler; Greg J. Bloy; Rachel N. Thessin; Stephanie K. Gaffney; Jonathan J. Lareau

2011-01-01T23:59:59.000Z

426

Can Climate Forecasts for the Growing Season be Valuable to Crop Producers: Some General Considerations and an Illinois Pilot Study  

Science Conference Proceedings (OSTI)

A three-step process is proposed to be most efficient for generating skillful climate forecasts which could reduce the adverse socioeconomic effects of climatic variability. These steps involve identifying weather-sensitive economic sectors, ...

Steven T. Sonka; Peter J. Lamb; Stanley A. Changnon Jr.; Aree Wiboonpongse

1982-04-01T23:59:59.000Z

427

Extracting Unique Information from High-Resolution Forecast Models: Monitoring Selected Fields and Phenomena Every Time Step  

Science Conference Proceedings (OSTI)

A new strategy for generating and presenting model diagnostic fields from convection-allowing forecast models is introduced. The fields are produced by computing temporal-maximum values for selected diagnostics at each horizontal grid point ...

John S. Kain; Scott R. Dembek; Steven J. Weiss; Jonathan L. Case; Jason J. Levit; Ryan A. Sobash

2010-10-01T23:59:59.000Z

428

Dynamics and Structure of Mesoscale Error Covariance of a Winter Cyclone Estimated through Short-Range Ensemble Forecasts  

Science Conference Proceedings (OSTI)

Several sets of short-range mesoscale ensemble forecasts generated with different types of initial perturbations are used in this study to investigate the dynamics and structure of mesoscale error covariance in an intensive extratropical ...

Fuqing Zhang

2005-10-01T23:59:59.000Z

429

Module Configuration  

SciTech Connect

A stand alone battery module including: (a) a mechanical configuration; (b) a thermal management configuration; (c) an electrical connection configuration; and (d) an electronics configuration. Such a module is fully interchangeable in a battery pack assembly, mechanically, from the thermal management point of view, and electrically. With the same hardware, the module can accommodate different cell sizes and, therefore, can easily have different capacities. The module structure is designed to accommodate the electronics monitoring, protection, and printed wiring assembly boards (PWAs), as well as to allow airflow through the module. A plurality of modules may easily be connected together to form a battery pack. The parts of the module are designed to facilitate their manufacture and assembly.

Oweis, Salah (Ellicott City, MD); D' Ussel, Louis (Bordeaux, FR); Chagnon, Guy (Cockeysville, MD); Zuhowski, Michael (Annapolis, MD); Sack, Tim (Cockeysville, MD); Laucournet, Gaullume (Paris, FR); Jackson, Edward J. (Taneytown, MD)

2002-06-04T23:59:59.000Z

430

Meese-Rogoff redux: Micro-based exchange-rate forecasting  

E-Print Network (OSTI)

Johnatban. "Exchange Rate Forecasting: The Errors We'veBased Exchange-Rate Forecasting By MARTIN D . D . EVANS ANDon longer-horizon forecasting, we examine forecasting over

Evans, MDD; Lyons, Richard K.

2005-01-01T23:59:59.000Z

431

The Past as Prologue? Business Cycles and Forecasting since the 1960s  

E-Print Network (OSTI)

Forecasters,” Journal of Forecasting, Vol. 28, No. 2, Mar,of Macroeconomic Forecasting” Journal of Macroeconomics,of Federal Reserve Forecasting,” Journal of Macroeconomics,

Bardhan, Ashok Deo; Hicks, Daniel; Kroll, Cynthia A.; Yu, Tiffany

2010-01-01T23:59:59.000Z

432

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

E-Print Network (OSTI)

and V. Letschert (2005). Forecasting Electricity Demand in8364 Material World: Forecasting Household ApplianceMcNeil, 2008). Forecasting Diffusion Forecasting Variables

Letschert, Virginie

2010-01-01T23:59:59.000Z

433

Quantile Forecasting of Commodity Futures' Returns: Are Implied Volatility Factors Informative?  

E-Print Network (OSTI)

This study develops a multi-period log-return quantile forecasting procedure to evaluate the performance of eleven nearby commodity futures contracts (NCFC) using a sample of 897 daily price observations and at-the-money (ATM) put and call implied volatilities of the corresponding prices for the period from 1/16/2008 to 7/29/2011. The statistical approach employs dynamic log-returns quantile regression models to forecast price densities using implied volatilities (IVs) and factors estimated through principal component analysis (PCA) from the IVs, pooled IVs and lagged returns. Extensive in-sample and out-of-sample analyses are conducted, including assessment of excess trading returns, and evaluations of several combinations of quantiles, model specifications, and NCFC's. The results suggest that the IV-PCA-factors, particularly pooled return-IV-PCA-factors, improve quantile forecasting power relative to models using only individual IV information. The ratio of the put-IV to the call-IV is also found to improve quantile forecasting performance of log returns. Improvements in quantile forecasting performance are found to be better in the tails of the distribution than in the center. Trading performance based on quantile forecasts from the models above generated significant excess returns. Finally, the fact that the single IV forecasts were outperformed by their quantile regression (QR) counterparts suggests that the conditional distribution of the log-returns is not normal.

Dorta, Miguel

2012-05-01T23:59:59.000Z

434

Impact assessment of smart meter grouping on the accuracy of forecasting algorithms  

Science Conference Proceedings (OSTI)

The increased penetration of smart meters generates huge amounts of fine-grained data, which may empower a new generation of energy related applications and services. Significant research efforts focus on the usage of such data to mainly improve the ... Keywords: forecast accuracy, meter reading analysis, smart grid systems, smart metering

Dejan Ili?; Per Goncalves da Silva; Stamatis Karnouskos; Malte Jacobi

2013-03-01T23:59:59.000Z

435

Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumption to the Annual Energy Outlook Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

436

Development of the TRANSIMS environmental module  

DOE Green Energy (OSTI)

The TRansportation ANalysis and SIMulation System (TRANSIMS) is one part of the multi-track Travel Model Improvement Program sponsored by the US Department of Transportation, the Environmental Protection Agency, and Department of Energy. Los Alamos National Laboratory is leading this major effort to develop a new, integrated transportation and air quality forecasting procedures necessary to satisfy the Intermodal Surface Transportation Efficiency Act and the Clean Air Act and its amendments. TRANSIMS is a set of integrated analytical and simulation models and supporting data bases. The TRANSIMS methods deal with individual behavioral units and proceed through several steps to estimate travel. TRANSIMS predicts trips for individual households, residents and vehicles rather than for zonal aggregations of households. TRANSIMS also predicts the movement of individual freight loads. A regional microsimulation executes the generated trips on the transportation network, modeling the individual vehicle interactions and predicting the transportation system performance. The purpose of the environmental module is to translate traveler behavior into consequent air quality, energy consumption, and carbon dioxide emissions. Transportation systems play a significant role in urban air quality, energy consumption, and carbon-dioxide emissions.

Williams, M.D.; Thayer, G.; Smith, L.R. [Los Alamos National Lab., NM (United States). Technology and Safety Assessment Div.

1997-05-01T23:59:59.000Z

437

Use of wind power forecasting in operational decisions.  

DOE Green Energy (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

438

Mathematical and computer modelling reports: Modeling and forecasting energy markets with the intermediate future forecasting system  

Science Conference Proceedings (OSTI)

This paper describes the Intermediate Future Forecasting System (IFFS), which is the model used to forecast integrated energy markets by the U.S. Energy Information Administration. The model contains representations of supply and demand for all of the ...

Frederic H. Murphy; John J. Conti; Susan H. Shaw; Reginald Sanders

1989-09-01T23:59:59.000Z

439

BMA Probabilistic Quantitative Precipitation Forecasting over the Huaihe Basin Using TIGGE Multi-model Ensemble Forecasts  

Science Conference Proceedings (OSTI)

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

Jianguo Liu; Zhenghui Xie

440

Using National Air Quality Forecast Guidance to Develop Local Air Quality Index Forecasts  

Science Conference Proceedings (OSTI)

The National Air Quality Forecast Capability (NAQFC) currently provides next-day forecasts of ozone concentrations over the contiguous United States. It was developed collaboratively by NOAA and Environmental Protection Agency (EPA) in order to ...

Brian Eder; Daiwen Kang; S. Trivikrama Rao; Rohit Mathur; Shaocai Yu; Tanya Otte; Ken Schere; Richard Wayland; Scott Jackson; Paula Davidson; Jeff McQueen; George Bridgers

2010-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Role of Retrospective Forecasts of GCMs Forced with Persisted SST Anomalies in Operational Streamflow Forecasts Development  

Science Conference Proceedings (OSTI)

Seasonal streamflow forecasts contingent on climate information are essential for water resources planning and management as well as for setting up contingency measures during extreme years. In this study, operational streamflow forecasts are ...

A. Sankarasubramanian; Upmanu Lall; Susan Espinueva

2008-04-01T23:59:59.000Z

442

Evaluation of MJO Forecast Skill from Several Statistical and Dynamical Forecast Models  

Science Conference Proceedings (OSTI)

This work examines the performance of Madden–Julian oscillation (MJO) forecasts from NCEP’s coupled and uncoupled general circulation models (GCMs) and statistical models. The forecast skill from these methods is evaluated in near–real time. ...

Kyong-Hwan Seo; Wanqiu Wang; Jon Gottschalck; Qin Zhang; Jae-Kyung E. Schemm; Wayne R. Higgins; Arun Kumar

2009-05-01T23:59:59.000Z

443

A Probabilistic Forecast Contest and the Difficulty in Assessing Short-Range Forecast Uncertainty  

Science Conference Proceedings (OSTI)

Results are presented from a probability-based weather forecast contest. Rather than evaluating the absolute errors of nonprobabilistic temperature and precipitation forecasts, as is common in other contests, this contest evaluated the skill of ...

Thomas M. Hamill; Daniel S. Wilks

1995-09-01T23:59:59.000Z

444

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

Science Conference Proceedings (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

445

Implications of Ensemble Quantitative Precipitation Forecast Errors on Distributed Streamflow Forecasting  

Science Conference Proceedings (OSTI)

Evaluating the propagation of errors associated with ensemble quantitative precipitation forecasts (QPFs) into the ensemble streamflow response is important to reduce uncertainty in operational flow forecasting. In this paper, a multifractal ...

Giuseppe Mascaro; Enrique R. Vivoni; Roberto Deidda

2010-02-01T23:59:59.000Z

446

Evaluation of Probabilistic Precipitation Forecasts Determined from Eta and AVN Forecasted Amounts  

Science Conference Proceedings (OSTI)

This note examines the connection between the probability of precipitation and forecasted amounts from the NCEP Eta (now known as the North American Mesoscale model) and Aviation (AVN; now known as the Global Forecast System) models run over a 2-...

William A. Gallus Jr.; Michael E. Baldwin; Kimberly L. Elmore

2007-02-01T23:59:59.000Z

447

Reliable Probabilistic Quantitative Precipitation Forecasts from a Short-Range Ensemble Forecasting System  

Science Conference Proceedings (OSTI)

A simple binning technique is developed to produce reliable 3-h probabilistic quantitative precipitation forecasts (PQPFs) from the National Centers for Environmental Prediction (NCEP) multimodel short-range ensemble forecasting system obtained ...

David J. Stensrud; Nusrat Yussouf

2007-02-01T23:59:59.000Z

448

The Impact of Writing Area Forecast Discussions on Student Forecaster Performance  

Science Conference Proceedings (OSTI)

A brief study is provided on the forecast performance of students who write a mock area forecast discussion (AFD) on a weekly basis. Student performance was tracked for one semester (11 weeks) during the University of Missouri—Columbia's local ...

Patrick S. Market

2006-02-01T23:59:59.000Z

449

An Operational Model for Forecasting Probability of Precipitation and Yes/No Forecast  

Science Conference Proceedings (OSTI)

An operational system for forecasting probability of precipitation (PoP) and yes/no forecast over 10 stations during monsoon season is developed. A perfect prog method (PPM) approach is followed for statistical interpretation of numerical weather ...

Ashok Kumar; Parvinder Maini; S. V. Singh

1999-02-01T23:59:59.000Z

450

Evaluation of Probabilistic Medium-Range Temperature Forecasts from the North American Ensemble Forecast System  

Science Conference Proceedings (OSTI)

Ensemble temperature forecasts from the North American Ensemble Forecast System were assessed for quality against observations for 10 cities in western North America, for a 7-month period beginning in February 2007. Medium-range probabilistic ...

Doug McCollor; Roland Stull

2009-02-01T23:59:59.000Z

451

Further Evaluation of the National Meterological Center's Medium-Range Forecast Model Precpitation Forecasts  

Science Conference Proceedings (OSTI)

Precipitation forecasts made by the National Meteorological Center's medium-range forecast (MRF) model are evaluated for the period, 1 March 1987 to 31 March 1989. As shown by Roads and Maisel, the MRF model wet bias was substantially alleviated ...

John O. Roads; T. Norman Maisal; Jordan Alpert

1991-12-01T23:59:59.000Z

452

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page inTenTionally lefT blank 91 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2012, DOE/EIA-M068(2012). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

453

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 95 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2011, DOE/EIA-M068(2011). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

454

Renewable Fuels Module This  

U.S. Energy Information Administration (EIA) Indexed Site

Fuels Module Fuels Module This page inTenTionally lefT blank 175 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources: biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind [1]. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve

455

R/ECON July 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON July 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 2000 NEW JERSEY of growth will decelerate over the forecast period. The R/ECON TM forecast for New Jersey in 2000 looks to decelerate over the course of the forecast. These forces will combine to push the unemployment rate to more

456

Increasing NOAA's computational capacity to improve global forecast modeling  

E-Print Network (OSTI)

1 Increasing NOAA's computational capacity to improve global forecast modeling A NOAA of the NWS's forecast products, even its regional forecast products, are constrained by the limitations of NOAA's global forecast model. Unfortunately, our global forecasts are less accurate than those from

Hamill, Tom

457

Forecasting Random Walks Under Drift Instability  

E-Print Network (OSTI)

Forecasting Random Walks Under Drift Instability? M. Hashem Pesaran University of Cambridge, CIMF, and USC Andreas Pick University of Cambridge, CIMF March 11, 2008 Abstract This paper considers forecast averaging when the same model is used... but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to using forecasts based on a single...

Pesaran, M Hashem; Pick, Andreas

458

Transportation Sector Module 2000 Vol 2, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2000-01-01T23:59:59.000Z

459

Transportation Sector Module 2000 Vol 1, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

John Maples

2000-01-01T23:59:59.000Z

460

Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint  

DOE Green Energy (OSTI)

The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

Florita, A.; Hodge, B. M.; Milligan, M.

2012-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Space-Time Wind Speed Forecasting for Improved Power System Dispatch  

E-Print Network (OSTI)

In order to support large scale integration of wind power, state-of-the-art wind speed forecasting methods should provide accurate and adequate information to enable efficient scheduling of wind power in electric energy systems. In this article, space-time wind forecasts are incorporated into power system economic dispatch models. First, we proposed a new space-time wind forecasting model, which generalizes and improves upon a so-called regime-switching space-time model by allowing the forecast regimes to vary with the dominant wind direction and with the seasons. Then, results from the new wind forecasting model are implemented into a power system economic dispatch model, which takes into account both spatial and temporal wind speed correlations. This, in turn, leads to an overall more cost-effective scheduling of system-wide wind generation portfolio. The potential economic benefits arise in the system-wide generation cost savings and in the ancillary service cost savings. This is illustrated in a test system in the northwest region of the U.S. Compared with persistent and autoregressive models, our proposed method could lead to annual integration cost savings on the scale of tens of millions of dollars in regions with high wind penetration, such as Texas and the Northwest. Key words: Power system economic dispatch; Power system operation; Space-time statistical model; Wind data; Wind speed forecasting.

Xinxin Zhu; Marc G. Genton; Yingzhong Gu; Le Xie

2012-01-01T23:59:59.000Z

462

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.

463

Solar future: 1978. [Market forecast to 1992  

SciTech Connect

The growth in sales of solar heating equipment is discussed. Some forecasts are made for the continued market growth of collectors, pool systems, and photovoltaics. (MOW)

Butt, S.H.

1978-03-01T23:59:59.000Z

464

Energy conservation and official UK energy forecasts  

SciTech Connect

Behind the latest United Kingdom (UK) official forecasts of energy demand are implicit assumptions about future energy-price elasticities. Mr. Pearce examines the basis of the forecasts and finds that the long-term energy-price elasticities that they imply are two or three times too low. The official forecasts substantially understate the responsiveness of demand to energy price rises. If more-realistic price elasticities were assumed, the official forecasts would imply a zero primary energy-demand growth to 2000. This raises the interesting possibility of a low energy future being brought about entirely by market forces. 15 references, 3 tables.

Pearce, D.

1980-09-01T23:59:59.000Z

465

Geothermal wells: a forecast of drilling activity  

DOE Green Energy (OSTI)

Numbers and problems for geothermal wells expected to be drilled in the United States between 1981 and 2000 AD are forecasted. The 3800 wells forecasted for major electric power projects (totaling 6 GWe of capacity) are categorized by type (production, etc.), and by location (The Geysers, etc.). 6000 wells are forecasted for direct heat projects (totaling 0.02 Quads per year). Equations are developed for forecasting the number of wells, and data is presented. Drilling and completion problems in The Geysers, The Imperial Valley, Roosevelt Hot Springs, the Valles Caldera, northern Nevada, Klamath Falls, Reno, Alaska, and Pagosa Springs are discussed. Likely areas for near term direct heat projects are identified.

Brown, G.L.; Mansure, A.J.; Miewald, J.N.

1981-07-01T23:59:59.000Z

466

Time Series Prediction Forecasting the Future and ...  

Science Conference Proceedings (OSTI)

Time Series Prediction Forecasting the Future and Understanding the Past Santa Fe Institute Proceedings on the Studies in the Sciences of ...

2012-10-01T23:59:59.000Z

467

Promotional forecasting in the grocery retail business  

E-Print Network (OSTI)

Predicting customer demand in the highly competitive grocery retail business has become extremely difficult, especially for promotional items. The difficulty in promotional forecasting has resulted from numerous internal ...

Koottatep, Pakawkul

2006-01-01T23:59:59.000Z

468

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

SciTech Connect

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

469

Forecasting Prices andForecasting Prices and Congestion forCongestion for  

E-Print Network (OSTI)

Abstract--In deregulated electricity markets, short-term load forecasting is important for reliable power322 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 25, NO. 1, FEBRUARY 2010 Short-Term Load Forecasting presents a similar day-based wavelet neural network method to forecast tomorrow's load. The idea

Tesfatsion, Leigh

470

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations  

E-Print Network (OSTI)

Power Forecasting in Five U.S. Electricity Markets MISO NYISO PJM ERCOT CAISO Peak load 109,157 MW (7 ........................................................................................... 18 4 WIND POWER FORECASTING AND ELECTRICITY MARKET OPERATIONS............................................................ 18 4-1 Market Operation and Wind Power Forecasting in Five U.S. Electricity Markets .......... 21 #12

Kemner, Ken

471

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

472

Forecasting during the Lake-ICE/SNOWBANDS Field Experiments  

Science Conference Proceedings (OSTI)

Despite improvements in numerical weather prediction models, statistical models, forecast decision trees, and forecasting rules of thumb, human interpretation of meteorological information for a particular forecast situation can still yield a ...

Peter J. Sousounis; Greg E. Mann; George S. Young; Richard B. Wagenmaker; Bradley D. Hoggatt; William J. Badini

1999-12-01T23:59:59.000Z

473

Experiments in Temperature and Precipitation Forecasting for Illinois  

Science Conference Proceedings (OSTI)

Six years of daily temperature and precipitation forecasting are studied for Urbana, Illinois. Minimum temperature forecast skills, measured against a climatological control, are 57%, 48%, 34% and 20% for the respective forecast ranges of one, ...

John R. Gyakum

1986-06-01T23:59:59.000Z

474

The Economic Value Of Ensemble-Based Weather Forecasts  

Science Conference Proceedings (OSTI)

The potential economic benefit associated with the use of an ensemble of forecasts versus anequivalent or higher-resolution control forecast is discussed. Neither forecast systems are post-processed,except a simple calibration that is applied to ...

Yuejian Zhu; Zoltan Toth; Richard Wobus; David Richardson; Kenneth Mylne

2002-01-01T23:59:59.000Z

475

A Probabilistic Forecast Approach for Daily Precipitation Totals  

Science Conference Proceedings (OSTI)

Commonly, postprocessing techniques are employed to calibrate a model forecast. Here, a probabilistic postprocessor is presented that provides calibrated probability and quantile forecasts of precipitation on the local scale. The forecasts are ...

Petra Friederichs; Andreas Hense

2008-08-01T23:59:59.000Z

476

Uses and Applications of Climate Forecasts for Power Utilities  

Science Conference Proceedings (OSTI)

The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-...

Stanley A. Changnon; Joyce M. Changnon; David Changnon

1995-05-01T23:59:59.000Z

477

Forecasting and Verifying in a Field Research Project: DOPLIGHT '87  

Science Conference Proceedings (OSTI)

Verification of forecasts during research field experiments is discussed and exemplified using the DOPLIGHT '87 experiment. We stress the importance of forecast verification if forecasting is to be a serious component of the research. A direct ...

Charles A. Doswell III; John A. Flueck

1989-06-01T23:59:59.000Z

478

Diversity in Interpretations of Probability: Implications for Weather Forecasting  

Science Conference Proceedings (OSTI)

Over the last years, probability weather forecasts have become increasingly popular due in part to the development of ensemble forecast systems. Despite its widespread use in atmospheric sciences, probability forecasting remains a subtle and ...

Ramón de Elía; René Laprise

2005-05-01T23:59:59.000Z

479

An Alternative Tropical Cyclone Intensity Forecast Verification Technique  

Science Conference Proceedings (OSTI)

The National Hurricane Center (NHC) does not verify official or model forecasts if those forecasts call for a tropical cyclone to dissipate or if the real tropical cyclone dissipates. A new technique in which these forecasts are included in a ...

Sim D. Aberson

2008-12-01T23:59:59.000Z

480

On the Reliability and Calibration of Ensemble Forecasts  

Science Conference Proceedings (OSTI)

An important aspect of ensemble forecasting is that the resulting probabilities are reliable (i.e., the forecast probabilities match the observed frequencies). In the medium-range forecasting context, the literature tends to focus on the ...

Christine Johnson; Neill Bowler

2009-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "module generates forecasts" 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

Scoring Probabilistic Forecasts: The Importance of Being Proper  

Science Conference Proceedings (OSTI)

Questions remain regarding how the skill of operational probabilistic forecasts is most usefully evaluated or compared, even though probability forecasts have been a long-standing aim in meteorological forecasting. This paper explains the ...

Jochen Bröcker; Leonard A. Smith

2007-04-01T23:59:59.000Z

482

Prediction of Consensus Tropical Cyclone Track Forecast Error  

Science Conference Proceedings (OSTI)

The extent to which the tropical cyclone (TC) track forecast error of a consensus model (CONU) routinely used by the forecasters at the National Hurricane Center can be predicted is determined. A number of predictors of consensus forecast error, ...

James S. Goerss

2007-05-01T23:59:59.000Z

483

An Experiment in Mesoscale Weather Forecasting in the Michigan Area  

Science Conference Proceedings (OSTI)

During an experiment in mesoscale weather forecasting in the Michigan area, consensus improved over NWS guidance in maximum/minimum temperature and probability of precipitation forecasts out to 24 hours. Forecasts were generally best in the ...

Dennis G. Baker

1986-12-01T23:59:59.000Z

484

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System  

Science Conference Proceedings (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

NONE

1998-01-01T23:59:59.000Z

485

THE EFFECT OF ACOUSTIC MODULATION ON SPRAY ...  

Science Conference Proceedings (OSTI)

... that at full load in liquid injection systems, extra energy or perturbation is ... The acoustic modulation is generated by a piezoelectric crystal driven by a ...

486

forecasts  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 106. Average annual minemouth coal prices by region, 1990-2040 (2011 dollars per million Btu) Appalachia Interior West US Average

487

Price and Load Forecasting in Volatile Energy Markets  

Science Conference Proceedings (OSTI)

With daily news stories about wildly fluctuating electricity prices and soaring natural gas prices, forecasters' responsibilities are expanding, visibility is increasing, and pressure exists to produce more frequent forecasts and more kinds of forecasts. The proceedings of EPRI's 13th Forecasting Symposium, held November 13-15 in Nashville, Tennessee, address current forecasting issues and developments, as well as explain the role that forecasters have played in recent events in energy markets.

2001-12-05T23:59:59.000Z

488

Module Handbook Specialisation Photovoltaics  

E-Print Network (OSTI)

#12;Specialisation Photovoltaics, University of Northumbria Module 1/Photovoltaics: PHOTOVOLTAIC CELL AND MODULE TECHNOLOGY Module name: PHOTOVOLTAIC CELL AND MODULE TECHNOLOGY Section EUREC · Chemistry · Physics Target learning outcomes The module Photovoltaic Cell and Module Technology teaches

Habel, Annegret

489

Blasting Vibration Forecast Base on Neural Network  

Science Conference Proceedings (OSTI)

The influence of blasting vibration to surroundings around the blasting area can not be ignored, in order to guarantee the safety of surroundings around blasting area, blasting vibration forecasting model based on neural network is established by improved ... Keywords: Blasting vibration, Neural network, Forecast

Haiwang Ye; Fang Liu; Jian Chang; Lin Feng; Yang Wang; Peng Yao; Kai Wu

2010-10-01T23:59:59.000Z

490

Evaluating the Skill of Categorical Forecasts  

Science Conference Proceedings (OSTI)

A generalized skill score is presented for evaluating forecasts in any number of categories. Each forecast in a sample is given a mark; the skill score for the sample is just the average mark. Each mark has an expected value of zero for an ...

Neil D. Gordon

1982-07-01T23:59:59.000Z

491

Forecasting demand of commodities after natural disasters  

Science Conference Proceedings (OSTI)

Demand forecasting after natural disasters is especially important in emergency management. However, since the time series of commodities demand after natural disasters usually has a great deal of nonlinearity and irregularity, it has poor prediction ... Keywords: ARIMA, Demand forecasting, EMD, Emergency management, Natural disaster

Xiaoyan Xu; Yuqing Qi; Zhongsheng Hua

2010-06-01T23:59:59.000Z

492

Time series forecasting with Qubit Neural Networks  

Science Conference Proceedings (OSTI)

This paper proposes a quantum learning scheme approach for time series forecasting, through the application of the new non-standard Qubit Neural Network (QNN) model. The QNN description was adapted in this work in order to resemble classical Artificial ... Keywords: artificial intelligence, artificial neural networks, quantum computing, qubit neural networks, time series forecasting

Carlos R. B. Azevedo; Tiago A. E. Ferreira

2007-08-01T23:59:59.000Z

493

Making Forecasts and Weather Normalization Work Together  

Science Conference Proceedings (OSTI)

Electric utility industry restructuring has changed the consistency between weather-normalized sales and energy forecasts. This Technology Review discusses the feasibility of integrating weather normalization and forecasting processes, and addresses whether the conflicting goal of obtaining greater consistency and accuracy with fewer staff resources can be met with more integrated approaches.

2000-09-11T23:59:59.000Z

494

A spatially distributed flash flood forecasting model  

Science Conference Proceedings (OSTI)

This paper presents a distributed model that is in operational use for forecasting flash floods in northern Austria. The main challenge in developing the model was parameter identification which was addressed by a modelling strategy that involved a model ... Keywords: Distributed modelling, Dominant processes concept, Floods, Forecasting, Kalman Filter, Model accuracy, Parameter identification, Stream routing

Günter Blöschl; Christian Reszler; Jürgen Komma

2008-04-01T23:59:59.000Z

495

The NCEP Climate Forecast System Version 2  

Science Conference Proceedings (OSTI)

The second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled Reanalysis ...

Suranjana Saha; Shrinivas Moorthi; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; David Behringer; Yu-Tai Hou; Hui-ya Chuang; Mark Iredell; Michael Ek; Jesse Meng; Rongqian Yang; Malaquías Peńa Mendez; Huug van den Dool; Qin Zhang; Wanqiu Wang; Mingyue Chen; Emily Becker

496

Forecast of geothermal-drilling activity  

DOE Green Energy (OSTI)

The number of geothermal wells that will be drilled to support electric power production in the United States through 2000 A.D. are forecasted. Results of the forecast are presented by 5-year periods for the five most significant geothermal resources.

Mansure, A.J.; Brown, G.L.

1982-07-01T23:59:59.000Z

497

Preemptive Forecasts Using an Ensemble Kalman Filter  

Science Conference Proceedings (OSTI)

An ensemble Kalman filter (EnKF) estimates the error statistics of a model forecast using an ensemble of model forecasts. One use of an EnKF is data assimilation, resulting in the creation of an increment to the first-guess field at the ...

Brian J. Etherton

2007-10-01T23:59:59.000Z

498

Incentives for Retailer Forecasting: Rebates vs. Returns  

Science Conference Proceedings (OSTI)

This paper studies a manufacturer that sells to a newsvendor retailer who can improve the quality of her demand information by exerting costly forecasting effort. In such a setting, contracts play two roles: providing incentives to influence the retailer's ... Keywords: endogenous adverse selection, forecasting, rebates, returns, supply chain contracting

Terry A. Taylor; Wenqiang Xiao

2009-10-01T23:59:59.000Z

499

Efficient forecasting for hierarchical time series  

Science Conference Proceedings (OSTI)

Forecasting is used as the basis for business planning in many application areas such as energy, sales and traffic management. Time series data used in these areas is often hierarchically organized and thus, aggregated along the hierarchy levels based ... Keywords: forecasting, hierarchies, optimization, time series

Lars Dannecker; Robert Lorenz; Philipp Rösch; Wolfgang Lehner; Gregor Hackenbroich

2013-10-01T23:59:59.000Z

500

Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumption to the Annual Energy Outlook Petroleum Market Module Figure 8. Petroleum Administration for Defense Districts. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohols, ethers, and bioesters natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of U.S. refining