National Library of Energy BETA

Sample records for forecasting system iffs

  1. Massachusetts state airport system plan forecasts.

    E-Print Network [OSTI]

    Mathaisel, Dennis F. X.

    This report is a first step toward updating the forecasts contained in the 1973 Massachusetts State System Plan. It begins with a presentation of the forecasting techniques currently available; it surveys and appraises the ...

  2. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22

    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...

  3. Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)

    SciTech Connect (OSTI)

    Hodge, B. M.; Ela, E.; Milligan, M.

    2011-10-01

    This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

  4. Condensed matter physics IFF Scientific Report 2009 Phase change memory materials: an

    E-Print Network [OSTI]

    Condensed matter physics · IFF Scientific Report 2009 6464 Phase change memory materials: an update supercomputers. Phase change (PC) materials are familiar to us all as rewritable media (CD-RW, DVD-RW, DVD.70Te0.30) are also in common use, particularly in DVD-RW systems. We discuss alloys from both

  5. Solar Forecasting System and Irradiance Variability Characterization

    E-Print Network [OSTI]

    solar forecasting system based on numerical weather prediction plus satellite and ground-based data.1 Photovoltaic Systems: Report 3 Development of data base allowing managed access to statewide PV and insolation Based Data 13 Summary 14 References 14 #12;List of Figures Figure Number and Title Page # 1. Topography

  6. Steam System Forecasting and Management 

    E-Print Network [OSTI]

    Mongrue, D. M.; Wittke, D. O.

    1982-01-01

    Union Carbide's Taft Plant is a typical petrochemical complex with several processes that use and produce various fuel and steam resources. The plant steam and fuel system balances vary extensively since several process units 'block operate...

  7. SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS Detlev Heinemann Oldenburg in irradiance forecasting have been presented more than twenty years ago (Jensenius and Cotton, 1981), when or progress with respect to the development of solar irradiance forecasting methods. Heck and Takle (1987

  8. Electric Grid - Forecasting system licensed | ornl.gov

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

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

  9. Science and Engineering of an Operational Tsunami Forecasting System

    SciTech Connect (OSTI)

    Gonzalez, Frank

    2009-04-06

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  10. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  11. Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems

    E-Print Network [OSTI]

    Shenoy, Prashant

    Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems Navin Sharma,gummeson,irwin,shenoy}@cs.umass.edu Abstract--To sustain perpetual operation, systems that harvest environmental energy must carefully regulate their usage to satisfy their demand. Regulating energy usage is challenging if a system's demands

  12. Weather forecast-based optimization of integrated energy systems.

    SciTech Connect (OSTI)

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

    2009-03-01

    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.

  13. Large-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random Fields

    E-Print Network [OSTI]

    Kolter, J. Zico

    in a wide range of energy systems, including forecasting demand, renewable generation, and electricityLarge-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random demonstrated that in the context of electrical demand and wind power, probabilistic forecasts can offer

  14. Oceanic stochastic parametrizations in a seasonal forecast system

    E-Print Network [OSTI]

    Andrejczuk, M; Juricke, S; Palmer, T N; Weisheimer, A; Zanna, L

    2015-01-01

    We study the impact of three stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the Stochastically Perturbed Parametrization Tendency (SPPT) scheme - which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely the western boundary currents and the Southern Ocean. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.

  15. Quality Assessment of the Cobel-Isba Numerical Forecast System of Fog and Low Clouds

    E-Print Network [OSTI]

    Quality Assessment of the Cobel-Isba Numerical Forecast System of Fog and Low Clouds THIERRY BERGOT Abstract--Short-term forecasting of fog is a difficult issue which can have a large societal impact. Fog of the life cycle of fog (onset, development and dissipation) up to +6 h. The error on the forecast onset

  16. Streamflow forecasting for large-scale hydrologic systems 

    E-Print Network [OSTI]

    Awwad, Haitham Munir

    1991-01-01

    Farland (Member) J esTR ao (Head of Department) May 1991 ABSTRACT Streamflow Forecasting for Large-Scale Hydrologic Systems. (May 1991) Haitham Munir Awwad, B. S. , University of Jordan Chair of Advisory Committee: Dr. Juan B. Valdes An on-line streamflow... thankful to Dr. Ralph A. Wurbs and Dr. Marshall J. McFarland for their assistance on my advisory committee. Support for this thesis by the Department of Civil Engineering through the Engineering Excellence Fund, and by the U, S. Army Corps of Engineers...

  17. Traffic congestion forecasting model for the INFORM System. Final report

    SciTech Connect (OSTI)

    Azarm, A.; Mughabghab, S.; Stock, D.

    1995-05-01

    This report describes a computerized traffic forecasting model, developed by Brookhaven National Laboratory (BNL) for a portion of the Long Island INFORM Traffic Corridor. The model has gone through a testing phase, and currently is able to make accurate traffic predictions up to one hour forward in time. The model will eventually take on-line traffic data from the INFORM system roadway sensors and make projections as to future traffic patterns, thus allowing operators at the New York State Department of Transportation (D.O.T.) INFORM Traffic Management Center to more optimally manage traffic. It can also form the basis of a travel information system. The BNL computer model developed for this project is called ATOP for Advanced Traffic Occupancy Prediction. The various modules of the ATOP computer code are currently written in Fortran and run on PC computers (pentium machine) faster than real time for the section of the INFORM corridor under study. The following summarizes the various routines currently contained in the ATOP code: Statistical forecasting of traffic flow and occupancy using historical data for similar days and time (long term knowledge), and the recent information from the past hour (short term knowledge). Estimation of the empirical relationships between traffic flow and occupancy using long and short term information. Mechanistic interpolation using macroscopic traffic models and based on the traffic flow and occupancy forecasted (item-1), and the empirical relationships (item-2) for the specific highway configuration at the time of simulation (construction, lane closure, etc.). Statistical routine for detection and classification of anomalies and their impact on the highway capacity which are fed back to previous items.

  18. IT/Nano IFF Scientific Report 2007 Nanoscale Phase Transitions in Phase

    E-Print Network [OSTI]

    IT/Nano · IFF Scientific Report 2007 158 I 159 Nanoscale Phase Transitions in Phase Change, and phase change (PC) materials are familiar to us as rewritable media (CD-RW, DVD- RW, DVD-RAM). Recently commercially available DVD-RW stor- age devices and DVD-RAM, are based on films of alloys of Ge, Sb, and Te

  19. AN OPERATOR IS A PRODUCT OF TWO QUASINILPOTENT OPERATORS IFF IT IS NOT SEMIFREDHOLM

    E-Print Network [OSTI]

    Müller, Vladimír

    AN OPERATOR IS A PRODUCT OF TWO QUASI­NILPOTENT OPERATORS IFF IT IS NOT SEMI­FREDHOLM ROMAN operators. The essential spectrum #27; e (T ), left essential spectrum #27; le (T ) and right essential spectrum #27; re (T ) of an operator T 2 B(H) is defined as the spectrum, left spectrum and right spectrum

  20. Seasonal Sensitivity on COBEL-ISBA Local Forecast System for Fog and Low Clouds

    E-Print Network [OSTI]

    Seasonal Sensitivity on COBEL-ISBA Local Forecast System for Fog and Low Clouds STEVIE ROQUELAURE of uncertainty that lead to dispersion. Key words: Local numerical forecast system, fog and low clouds, seasonal prediction system. 1. Introduction Accurate prediction of fog and low clouds is one of the main issues

  1. A Novel Forecasting System for Solar Particle Events and Flares (FORSPEF)

    E-Print Network [OSTI]

    Anastasiadis, Anastasios

    A Novel Forecasting System for Solar Particle Events and Flares (FORSPEF) A Papaioannou1 Energetic Particles (SEPs) result from intense solar eruptive events such as solar flares and coronal mass. In this work, we present FORSPEF (Forecasting Solar Particle Events and Flares), a novel dual system, designed

  2. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore »larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  3. Viability, Development, and Reliability Assessment of Coupled Coastal Forecasting Systems 

    E-Print Network [OSTI]

    Singhal, Gaurav

    2012-10-19

    Real-time wave forecasts are critical to a variety of coastal and offshore opera- tions. NOAA’s global wave forecasts, at present, do not extend into many coastal regions of interest. Even after more than two decades of the historical Exxon Valdez...

  4. Towards a Self-Configurable Weather Research and Forecasting System Khalid Saleem, S. Masoud Sadjadi, Shu-Ching Chen

    E-Print Network [OSTI]

    Chen, Shu-Ching

    Towards a Self-Configurable Weather Research and Forecasting System Khalid Saleem, S. Masoud, Miami FL {ksale002, sadjadi,chens}@cs.fiu.edu ABSTRACT Current weather forecast and visualization systems lack the scalability to support numerous customized requests for weather research and forecasting

  5. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE: Preprint

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B. M.

    2014-09-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This study examines the value of improved solar power forecasting for the Independent System Operator-New England system. The results show how 25% solar power penetration reduces net electricity generation costs by 22.9%.

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

    SciTech Connect (OSTI)

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

    2009-01-01

    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.

  7. Development of Load Forecasting Procedures for the Texas A&M University System 

    E-Print Network [OSTI]

    Baltazar-Cervantes, J. C.; Lim, C.; Haberl, J. S.; Turnder, W. D.; Claridge, D. E.

    2001-01-01

    This paper reports on the effort to develop load-forecasting procedures for the Texas A&M University System (TAMUS). Such procedures are being investigated to determine if the TAMUS can benefit from the pending deregulation ...

  8. QUALIFIED FORECAST OF ENSEMBLE POWER PRODUCTION BY SPATIALLY DISPERSED GRID-CONNECTED PV SYSTEMS

    E-Print Network [OSTI]

    Heinemann, Detlev

    , Energy Meteorology Group, D-26111 Oldenburg, Germany, elke.lorenz@uni-oldenburg.de + UniversityQUALIFIED FORECAST OF ENSEMBLE POWER PRODUCTION BY SPATIALLY DISPERSED GRID- CONNECTED PV SYSTEMS Schneider° * University of Oldenburg, Institute of Physics, Energy and Semiconductor Research Laboratory

  9. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE (Presentation)

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B.M.

    2014-11-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This presentation is an overview of a study that examines the value of improved solar forecasts on Bulk Power System Operations.

  10. Weather Forecast Data an Important Input into Building Management Systems 

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01

    Implementation and Operational Services Section Canadian Meteorological Centre, Dorval, Qc National Prediction Operations Division ICEBO 2013, Montreal, Qc October 10 2013 Version 2013-09-27 Weather Forecast Data An Important Input into Building..., Martin Fradette Environment Canada RPN ? Recherche en Pr?vision num?rique Dr. Wei Yu, Dr. Paul Vaillancourt, Dr. Sylvie Leroyer Natural Resources Canada ? Canmet Energy Dr. Jos? A. Candanedo Overview ? Building management and weather information...

  11. Intercomparison of mesoscale meteorological models for precipitation forecasting Hydrology and Earth System Sciences, 7(6), 799811 (2003) EGU

    E-Print Network [OSTI]

    Boyer, Edmond

    2003-01-01

    Intercomparison of mesoscale meteorological models for precipitation forecasting 799 Hydrology and Earth System Sciences, 7(6), 799811 (2003) © EGU Intercomparison of mesoscale meteorological models

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

    SciTech Connect (OSTI)

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

    2012-08-01

    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.

  13. Real-Time Forecasting for the Antarctic: An Evaluation of the Antarctic Mesoscale Prediction System (AMPS)*

    E-Print Network [OSTI]

    Howat, Ian M.

    Real-Time Forecasting for the Antarctic: An Evaluation of the Antarctic Mesoscale Prediction System. MANNING AND JORDAN G. POWERS Mesoscale and Microscale Meteorology Division, National Center.S. Antarctic Program's field operations, the Antarctic Mesoscale Prediction System (AMPS) was implemented in Oc

  14. AN OPERATOR IS A PRODUCT OF TWO QUASI-NILPOTENT OPERATORS IFF IT IS NOT SEMI-FREDHOLM

    E-Print Network [OSTI]

    Müller, Vladimír

    AN OPERATOR IS A PRODUCT OF TWO QUASI-NILPOTENT OPERATORS IFF IT IS NOT SEMI-FREDHOLM ROMAN operators. The essential spectrum e(T), left essential spectrum le(T) and right essential spectrum re(T) of an operator T B(H) is defined as the spectrum, left spectrum and right spectrum of the class T + K

  15. An Investigation of the Limitations in Plume Rise Models used in Air Quality Forecast Systems

    E-Print Network [OSTI]

    Collins, Gary S.

    are important for predicting pollutants regulated by National Ambient Air Quality Standards (NAAQS). NAAQS pollutants, include CO, NO2, PM2.5, PM10, O3, and SO2, are considered deleterious to public health and airAn Investigation of the Limitations in Plume Rise Models used in Air Quality Forecast Systems 1

  16. ENVIRONMENTAL INFORMATION SYSTEM FOR ANALYSIS AND FORECAST OF AIR POLLUTION (APPLICATION TO SANTIAGO DE CHILE)

    E-Print Network [OSTI]

    Bertossi, Leopoldo

    Chile and other cities in Chile, air pollution is a dramatic problem. An Environmental InformationENVIRONMENTAL INFORMATION SYSTEM FOR ANALYSIS AND FORECAST OF AIR POLLUTION (APPLICATION planning. Using a model-based EIS for air pollution it is possible (i) to study complex source

  17. Incorporating Optics into a Coupled Physical-Biological Forecasting System in the Monterey Bay

    E-Print Network [OSTI]

    Boss, Emmanuel S.

    Incorporating Optics into a Coupled Physical-Biological Forecasting System in the Monterey Bay Fei://www.marine.maine.edu/~eboss/index.html http://ourocean.jpl.nasa.gov/ LONG-TERM GOALS Modeling and predicting ocean optical properties for coastal waters requires linking optical properties with the physical, chemical, and biological processes

  18. Linear Diagnostics to Assess the Performance of an Ensemble Forecast System 

    E-Print Network [OSTI]

    Satterfield, Elizabeth A.

    2011-10-21

    frequency. We find that turning the digital filter on in these two sets of experiments leads to a major improvement of the analyses. In the experiments with randomly placed observations, turning the digital fil- ter on degrades the analysis in the Tropics... are carried out with an implementation of the Local En- semble Transform Kalman Filter (LETKF) data assimilation system on a reduced (T62L28) resolution version of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS). Both...

  19. Natural gas transmission and distribution model of the National Energy Modeling System

    SciTech Connect (OSTI)

    1997-02-01

    The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. From 1982 through 1993, the Intermediate Future Forecasting System (IFFS) was used by the EIA for its analyses, and the Gas Analysis Modeling System (GAMS) was used within IFFS to represent natural gas markets. Prior to 1982, the Midterm Energy Forecasting System (MEFS), also referred to as the Project Independence Evaluation System (PIES), was employed. NEMS was developed to enhance and update EIA`s modeling capability by internally incorporating models of energy markets that had previously been analyzed off-line. In addition, greater structural detail in NEMS permits the analysis of a broader range of energy issues. The time horizon of NEMS is the midterm period (i.e., through 2015). In order to represent the regional differences in energy markets, the component models of NEMS function at regional levels appropriate for the markets represented, with subsequent aggregation/disaggregation to the Census Division level for reporting purposes.

  20. A Distributed Modeling System for Short-Term to Seasonal Ensemble Streamflow Forecasting in Snowmelt Dominated Basins

    SciTech Connect (OSTI)

    Wigmosta, Mark S.; Gill, Muhammad K.; Coleman, Andre M.; Prasad, Rajiv; Vail, Lance W.

    2007-12-01

    This paper describes a distributed modeling system for short-term to seasonal water supply forecasts with the ability to utilize remotely-sensed snow cover products and real-time streamflow measurements. Spatial variability in basin characteristics and meteorology is represented using a raster-based computational grid. Canopy interception, snow accumulation and melt, and simplified soil water movement are simulated in each computational unit. The model is run at a daily time step with surface runoff and subsurface flow aggregated at the basin scale. This approach allows the model to be updated with spatial snow cover and measured streamflow using an Ensemble Kalman-based data assimilation strategy that accounts for uncertainty in weather forecasts, model parameters, and observations used for updating. Model inflow forecasts for the Dworshak Reservoir in northern Idaho are compared to observations and to April-July volumetric forecasts issued by the Natural Resource Conservation Service (NRCS) for Water Years 2000 – 2006. October 1 volumetric forecasts are superior to those issued by the NRCS, while March 1 forecasts are comparable. The ensemble spread brackets the observed April-July volumetric inflows in all years. Short-term (one and three day) forecasts also show excellent agreement with observations.

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

    SciTech Connect (OSTI)

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

    2010-10-19

    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.

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

    SciTech Connect (OSTI)

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

    2011-06-23

    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.

  3. Data-driven spectral decomposition and forecasting of ergodic dynamical systems

    E-Print Network [OSTI]

    Giannakis, Dimitrios

    2015-01-01

    We develop a framework for dimension reduction, mode decomposition, and nonparametric forecasting of data generated by ergodic dynamical systems. This framework is based on a representation of the Koopman group of unitary operators in a smooth orthonormal basis of the L2 space of the dynamical system, acquired from time-ordered data through the diffusion maps algorithm. Using this representation, we compute Koopman eigenfunctions through a regularized advection-diffusion operator, and employ these eigenfunctions in dimension reduction maps with projectible dynamics and high smoothness for the given observation modality. In systems with pure point spectra, we construct a decomposition of the generator of the Koopman group into mutually commuting vector fields, which we reconstruct in data space through a representation of the pushforward map in the Koopman eigenfunction basis. We also use a special property of this basis, namely that the basis elements evolve as simple harmonic oscillators, to build nonparamet...

  4. FORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev Heinemann*, Hashini Wickramarathne*, Hans Georg Beyer +

    E-Print Network [OSTI]

    Heinemann, Detlev

    of Physics, Energy and Semiconductor Research Laboratory, Energy Meteorology Group, 26111 Oldenburg, GermanyH, Spicherer Straße 48, D-86157 Augsburg, Germany ABSTRACT: The contribution of power production by PV systemsFORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev Heinemann

  5. Weather Research and Forecasting Model's Community Variational/Ensemble Data Assimilation System: WRFDA

    SciTech Connect (OSTI)

    Barker, D.; Huang, X. Y.; Liu, Z. Q.; Auligne, T.; Zhang, X.; Rugg, S.; Ajjaji, R.; Bourgeois, A.; Bray, J.; Chen, Y. S.; Demirtas, M.; Guo, Y. R.; Henderson, T.; Huang, W.; Lin, H. C.; Michalakes, J.; Rizvi, S.; Zhang, X. Y.

    2012-06-01

    Data assimilation is the process by which observations are combined with short-range NWP model output to produce an analysis of the state of the atmosphere at a specified time. Since its inception in the late 1990s, the multiagency Weather Research and Forecasting (WRF) model effort has had a strong data assimilation component, dedicating two working groups to the subject. This article documents the history of the WRF data assimilation effort, and discusses the challenges associated with balancing academic, research, and operational data assimilation requirements in the context of the WRF effort to date. The WRF Model's Community Variational/Ensemble Data Assimilation System (WRFDA) has evolved over the past 10 years, and has resulted in over 30 refereed publications to date, as well as implementation in a wide range of real-time and operational NWP systems.

  6. Contributions from a Local Ensemble Prediction System (LEPS) for Improving Fog and Low Cloud Forecasts at Airports

    E-Print Network [OSTI]

    Contributions from a Local Ensemble Prediction System (LEPS) for Improving Fog and Low Cloud authorities with accurate forecasts of fog and cloud ceiling. A specific event, which is called a low with the prediction of infrequent events like fog and the life cycles of low clouds. At Paris' Charles de Gaulle (Cd

  7. Impact of forecasting error on the performance of capacitated multi-item production systems

    E-Print Network [OSTI]

    Xie, Jinxing

    in manufacturing planning and control. The quality of the master production schedule (MPS) can significantly managers optimize their production plans by selecting more reasonable forecasting methods and scheduling forecasting, order entry and production planning activities on the one hand, and the detailed planning

  8. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

    For the Solar Forecast Improvement Project (SFIP), the Earth System Research Laboratory (ESRL) is partnering with the National Center for Atmospheric Research (NCAR) and IBM to develop more...

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

    SciTech Connect (OSTI)

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

    2010-01-01

    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.

  10. Resource Information and Forecasting Group; Electricity, Resources, & Building Systems Integration (ERBSI) (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2009-11-01

    Researchers in the Resource Information and Forecasting group at NREL provide scientific, engineering, and analytical expertise to help characterize renewable energy resources and facilitate the integration of these clean energy sources into the electricity grid.

  11. Condensed matter physics IFF Scientific Report 2008 Nanoscale phase transitions in phase

    E-Print Network [OSTI]

    pulse is applied, and the state can be determined by monitoring the optical or electrical properties storage and memory materials [1] can be seen in Fig. 1. GeTe was the first system to show (1986) real-ray and neutron scattering experiments. Several calcula- tions have been performed in recent years, but the unit

  12. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect (OSTI)

    Hadder, G.R.; Davis, R.M.

    1991-09-01

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People`s Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  13. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect (OSTI)

    Hadder, G.R.; Davis, R.M.

    1991-09-01

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People's Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  14. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens to the Klim wind farm using three WPPT forecasts based on different weather forecasting systems. It is shown of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

  15. Solar Forecasting

    Broader source: Energy.gov [DOE]

    On December 7, 2012, DOE announced $8 million to fund two solar projects that are helping utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S....

  16. EWEC 2006 Scientific Track Advanced Forecast Systems for the Grid Integration of 25 GW

    E-Print Network [OSTI]

    Heinemann, Detlev

    forecasts, smoothing effects Abstract The economic success of offshore wind farms in liberalised electricity of offshore wind farms, their electricity production must be known well in advance to allow an efficient Oldenburg, Germany Key words: Offshore wind power, grid integration, short-term prediction, regional

  17. Downscaling Extended Weather Forecasts for Hydrologic Prediction

    SciTech Connect (OSTI)

    Leung, Lai-Yung R.; Qian, Yun

    2005-03-01

    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.

  18. Puget Sound Operational Forecast System - A Real-time Predictive Tool for Marine Resource Management and Emergency Responses

    SciTech Connect (OSTI)

    Yang, Zhaoqing; Khangaonkar, Tarang; Chase, Jared M.; Wang, Taiping

    2009-12-01

    To support marine ecological resource management and emergency response and to enhance scientific understanding of physical and biogeochemical processes in Puget Sound, a real-time Puget Sound Operational Forecast System (PS-OFS) was developed by the Coastal Ocean Dynamics & Ecosystem Modeling group (CODEM) of Pacific Northwest National Laboratory (PNNL). PS-OFS employs the state-of-the-art three-dimensional coastal ocean model and closely follows the standards and procedures established by National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). PS-OFS consists of four key components supporting the Puget Sound Circulation and Transport Model (PS-CTM): data acquisition, model execution and product archive, model skill assessment, and model results dissemination. This paper provides an overview of PS-OFS and its ability to provide vital real-time oceanographic information to the Puget Sound community. PS-OFS supports pacific northwest region’s growing need for a predictive tool to assist water quality management, fish stock recovery efforts, maritime emergency response, nearshore land-use planning, and the challenge of climate change and sea level rise impacts. The structure of PS-OFS and examples of the system inputs and outputs, forecast results are presented in details.

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

    SciTech Connect (OSTI)

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

    2010-06-27

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

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

    SciTech Connect (OSTI)

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

    2010-03-15

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

  1. Published in proceedings of the 15 th IMACS'97 World Congress, August 1997, Berlin, Germany, Wissenshaft & Technik Verlag, Vol. 4, pp. 571--576. The CTADEL Application Driver for Numerical Weather Forecast Systems

    E-Print Network [OSTI]

    van Engelen, Robert A.

    , Wissenshaft & Technik Verlag, Vol. 4, pp. 571--576. The CTADEL Application Driver for Numerical Weather@cs.leidenuniv.nl Keywords: code generation; high performance computing; numerical weather forecasting ABSTRACT The CTADEL numerical weather forecast system. As such, the CTADEL system can be viewed as a problem­solving environment

  2. Univariate Modeling and Forecasting of Monthly Energy Demand Time Series

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system demand time series based only on data for six years to forecast the demand for the seventh year. Both

  3. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    and forecasting of solar radiation data: a review,”forecasting of solar- radiation data,” Solar Energy, vol.sequences of global solar radiation data for isolated sites:

  4. A forecast-driven tactical planning model for a serial manufacturing system

    E-Print Network [OSTI]

    Chhaochhria, Pallav

    We examine tactical planning for a serial manufacturing system that produces a product family with many process steps and low volumes. The system is subject to uncertainty in demand, in the supply of raw materials, and in ...

  5. Forecasting and Capturing Emission Reductions Using Industrial Energy Management and Reporting Systems 

    E-Print Network [OSTI]

    Robinson, J.

    2010-01-01

    The Mandatory 2010 Green House Gas (GHG) Reporting Regulations and pending climate change legislation has increased interest in Energy Management and Reporting Systems (EMRS) as a means of both reducing and reporting GHG emissions. This paper...

  6. Hybrid Generation Systems Planning Expansion Forecast: A Critical State of the Art Review

    E-Print Network [OSTI]

    Brest, Université de

    renewable energy resources are random and weather/climatic conditions-dependant. In this challenging context technical and economical constraints. Index Terms--Hybrid energy systems, renewable power generation-friendly nature (i.e. renewable energies). Although renewable energy penetration in electricity is expected

  7. ANEMOS: Development of a Next Generation Wind Power Forecasting System for the Large-Scale Integration of Onshore &

    E-Print Network [OSTI]

    Heinemann, Detlev

    -Scale Integration of Onshore & Offshore Wind Farms. G. Kariniotakis* , D. Mayer, J. Moussafir, R. Chevallaz-line operation at onshore and offshore wind farms for prediction at a local, regional and national scale, for onshore and offshore wind power forecasting, exploiting both statistical and physical modeling approaches

  8. Predictability of European air quality: Assessment of 3 years of operational forecasts and analyses by the PREV'AIR system

    E-Print Network [OSTI]

    Menut, Laurent

    , is proved to improve ozone forecasts, especially when photochemical pollution episodes occur. The PREV'AIR and laws regarding the pollutants of utmost importance in relation to human health, air pollution is still- ments are still needed to manage and control the impacts of air pollution on health. [3] Facing

  9. LOAD FORECASTING Eugene A. Feinberg

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    , regression, artificial intelligence. 1. Introduction Accurate models for electric power load forecasting to make important decisions including decisions on pur- chasing and generating electric power, load for different operations within a utility company. The natures 269 #12;270 APPLIED MATHEMATICS FOR POWER SYSTEMS

  10. An Intelligent Solar Powered Battery Buffered EV Charging Station with Solar Electricity Forecasting and EV Charging Load Projection Functions

    E-Print Network [OSTI]

    Zhao, Hengbing; Burke, Andrew

    2014-01-01

    power source from inherent intermittent solar PV power.B. Solar PV Electricity Forecasting Fig. 1. Charging stationForecasting Power Output of Solar Photovoltaic System Using

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

    E-Print Network [OSTI]

    Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting SAMUEL RE, a need exists for accurate and updated fog and low-cloud forecasts. Couche Brouillard Eau Liquide (COBEL for the very short-term forecast of fog and low clouds. This forecast system assimilates local observations

  12. Wind Power Forecasting Data

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

    Operations Call 2012 Retrospective Reports 2012 Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email...

  13. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

  14. Forecasting Water Quality & Biodiversity

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

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability Platform Review Principle Investigator: Dr. Henriette I. Jager Organization: Oak Ridge National...

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

  16. Wind Power Forecasting Error Distributions: An International Comparison; Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

    2012-09-01

    Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

  17. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

    Fuel Price Forecasts INTRODUCTION Fuel prices affect electricity planning in two primary ways and water heating, and other end-uses as well. Fuel prices also influence electricity supply and price turbines. This second effect is the primary use of the fuel price forecast for the Council's Fifth Power

  18. Weather Forecasting Spring 2014

    E-Print Network [OSTI]

    Hennon, Christopher C.

    ATMS 350 Weather Forecasting Spring 2014 Professor : Dr. Chris Hennon Office : RRO 236C Phone : 232 of atmospheric physics and the ability to include this understanding into modern numerical weather prediction agencies, forecast tools, numerical weather prediction models, model output statistics, ensemble

  19. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    ....................................................................................................1-16 Energy Consumption Data...............................................1-15 Data Sources for Energy Demand Forecasting ModelsCALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report

  20. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  1. Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

    SciTech Connect (OSTI)

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

    2013-10-01

    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.

  2. General Logic-Systems and Consequence Operators

    E-Print Network [OSTI]

    Robert A. Herrmann

    2006-06-03

    In this paper, general logic-systems are investigated. It is shown that there are infinitely many finite consequence operators defined on a fixed language L that cannot be generated from a finite logic-system. It is shown that a set map is a finite consequence operator iff it is defined by a general logic-system.

  3. Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

    This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

  4. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    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.

  5. Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

    SciTech Connect (OSTI)

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

    2012-07-01

    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.

  6. Flood management in a complex river basin with a real-time decision support system based on hydrological forecasts

    E-Print Network [OSTI]

    Lenstra, Arjen K.

    ENAC/ Flood management in a complex river basin with a real-time decision support system based System MINDS proposes the optimal hydropower plants management for flood peak reduction PREDICTING FLOODS for population safety and! Computational program: Routing System MINERVE Run-off model Infiltration model

  7. Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence

    E-Print Network [OSTI]

    Lawrence, Ramon

    Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence Department of Computer Science on the application of neural networks in forecasting stock market prices. With their ability to discover patterns in nonlinear and chaotic systems, neural networks offer the ability to predict market directions more

  8. Improving automotive battery sales forecast

    E-Print Network [OSTI]

    Bulusu, Vinod

    2015-01-01

    Improvement in sales forecasting allows firms not only to respond quickly to customers' needs but also to reduce inventory costs, ultimately increasing their profits. Sales forecasts have been studied extensively to improve ...

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

    E-Print Network [OSTI]

    Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts ............................................................................................................................ 5 U.S. Natural Gas Commodity Prices

  10. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required in electricity demand is, of course, crucial to determining the need for new electricity resources and helping of any forecast of electricity demand and developing ways to reduce the risk of planning errors

  11. Consensus Coal Production Forecast for

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    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

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

    E-Print Network [OSTI]

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

    2000-01-01

    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...

  13. Short-Term Load Forecasting at the Local Level using Smart Meter Data

    E-Print Network [OSTI]

    Tronci, Enrico

    ]; electric vehicle integration [8]; and microgrid and virtual power plant applications [7], [11]. In addition, forecast uncertainty, power demand. I. INTRODUCTION Short-Term Load Forecasting (STLF) is the forecasting is considered to be critical for power system operation, particularly for energy balancing, energy market

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

    SciTech Connect (OSTI)

    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.

    2013-10-01

    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.

  15. Ozone ensemble forecast with machine learning Vivien Mallet,1,2

    E-Print Network [OSTI]

    Mallet, Vivien

    Ozone ensemble forecast with machine learning algorithms Vivien Mallet,1,2 Gilles Stoltz,3; published 13 March 2009. [1] We apply machine learning algorithms to perform sequential aggregation of ozone forecasts. The latter rely on a multimodel ensemble built for ozone forecasting with the modeling system

  16. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Rutledge, Steven

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary microbursts than in many previously documented microbursts. Alignment of Doppler radar data to reports of wind-related damage to electrical power infrastructure in Phoenix allowed a comparison of microburst wind damage

  17. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary and interpretation of information from National Weather Service watches and warnings by10 decision makers such an outlier to the regional severe weather climatology. An analysis of the synoptic and13 mesoscale

  18. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01

    System (REEPS 2.1) , developed by the Electric Power Research Institute (EPRI), is a forecasting model

  19. Forecast Technical Document Felling and Removals

    E-Print Network [OSTI]

    of local investment and business planning. Timber volume production will be estimated at sub. Planning of operations. Control of the growing stock. Wider reporting (under UKWAS). The calculation fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan

  20. A critical evaluation of the upper ocean heat budget in the Climate Forecast System Reanalysis data for the south central equatorial Pacific

    SciTech Connect (OSTI)

    Liu H.; Lin W.; Liu, X.; Zhang, M.

    2011-08-26

    Coupled ocean-atmospheric models suffer from the common bias of a spurious rain belt south of the central equatorial Pacific throughout the year. Observational constraints on key processes responsible for this bias are scarce. The recently available reanalysis from a coupled model system for the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) data is a potential benchmark for climate models in this region. Its suitability for model evaluation and validation, however, needs to be established. This paper examines the mixed layer heat budget and the ocean surface currents - key factors for the sea surface temperature control in the double Inter-Tropical Convergence Zone in the central Pacific - from 5{sup o}S to 10{sup o}S and 170{sup o}E to 150{sup o}W. Two independent approaches are used. The first approach is through comparison of CFSR data with collocated station observations from field experiments; the second is through the residual analysis of the heat budget of the mixed layer. We show that the CFSR overestimates the net surface flux in this region by 23 W m{sup -2}. The overestimated net surface flux is mainly due to an even larger overestimation of shortwave radiation by 44 W m{sup -2}, which is compensated by a surface latent heat flux overestimated by 14 W m{sup -2}. However, the quality of surface currents and the associated oceanic heat transport in CFSR are not compromised by the surface flux biases, and they agree with the best available estimates. The uncertainties of the observational data from field experiments are also briefly discussed in the present study.

  1. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat

    2015-08-05

    Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

  2. Online short-term solar power forecasting

    SciTech Connect (OSTI)

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

    2009-10-15

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

  3. FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake Erie

    E-Print Network [OSTI]

    FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake Forecasting System (GLCFS) can be used to validate wind forecasts for the Great Lakes using observed weather prediction step-coordinate Eta Model are able to forecast winds for the Great Lakes region, using

  4. Assessment and added value estimation of an ensemble approach with a focus on global radiation forecasts

    E-Print Network [OSTI]

    Bouallegue, Zied Ben

    2015-01-01

    The assessment of the high-resolution ensemble weather prediction system COSMO-DE-EPS is achieved with the perspective of using it for renewable energy applications. The performance of the ensemble forecast is explored focusing on global radiation, the main weather variable affecting solar power production, and on quantile forecasts, key probabilistic products for the energy sector. First, the ability of the ensemble system to capture and resolve the observation variability is assessed. Secondly, the potential benefit of the ensemble forecasting strategy compared to a single forecast approach is quantitatively estimated. A new metric called ensemble added value is proposed, aiming at a fair comparison of an ensemble forecast with a single forecast, when optimized to the users' needs. Hourly mean forecasts are verified against pyranometer measurements over verification periods covering 2013. The results show in particular that the added value of the ensemble approach is season-dependent and increases with the ...

  5. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

    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.

  6. U.S. Regional Demand Forecasts Using NEMS and GIS

    SciTech Connect (OSTI)

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

    2005-07-01

    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.

  7. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  8. Wind Power Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubicthe FOIA?ResourceMeasurement BuoyForecasting Sign

  9. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    s economy. Demand Forecasts The three energy futures wereto meet the forecast demand in each energy futurE2. e e1£~energy saved through improved appliance efficiencies. Also icit in our demand forecasts

  10. A Public-Private-Academic Partnership to Advance Solar Power Forecasting

    Broader source: Energy.gov [DOE]

    The University Corporation for Atmospheric  Research (UCAR) will develop a solar power forecasting system that advances the state of the science through cutting-edge research.

  11. FUSION METHODS BASED ON COMMON ORDER INVARIABILITY FOR META SEARCH ENGINE SYSTEMS

    E-Print Network [OSTI]

    Zhang, Minjie

    FUSION METHODS BASED ON COMMON ORDER INVARIABILITY FOR META SEARCH ENGINE SYSTEMS Xiaohua Yang Hui@ctit.zhnut.edu.cn hy92,minjie@uow.edu.au Abstract: Fusion is an important work for running meta search engine systems. A fusion algorithm is rational iff it can satisfy three conditions, i.e. the associativity, commutativity

  12. Coal supply/demand, 1980 to 2000. Task 3. Resource applications industrialization system data base. Final review draft. [USA; forecasting 1980 to 2000; sector and regional analysis

    SciTech Connect (OSTI)

    Fournier, W.M.; Hasson, V.

    1980-10-10

    This report is a compilation of data and forecasts resulting from an analysis of the coal market and the factors influencing supply and demand. The analyses performed for the forecasts were made on an end-use-sector basis. The sectors analyzed are electric utility, industry demand for steam coal, industry demand for metallurgical coal, residential/commercial, coal demand for synfuel production, and exports. The purpose is to provide coal production and consumption forecasts that can be used to perform detailed, railroad company-specific coal transportation analyses. To make the data applicable for the subsequent transportation analyses, the forecasts have been made for each end-use sector on a regional basis. The supply regions are: Appalachia, East Interior, West Interior and Gulf, Northern Great Plains, and Mountain. The demand regions are the same as the nine Census Bureau regions. Coal production and consumption in the United States are projected to increase dramatically in the next 20 years due to increasing requirements for energy and the unavailability of other sources of energy to supply a substantial portion of this increase. Coal comprises 85 percent of the US recoverable fossil energy reserves and could be mined to supply the increasing energy demands of the US. The NTPSC study found that the additional traffic demands by 1985 may be met by the railways by the way of improved signalization, shorter block sections, centralized traffic control, and other modernization methods without providing for heavy line capacity works. But by 2000 the incremental traffic on some of the major corridors was projected to increase very significantly and is likely to call for special line capacity works involving heavy investment.

  13. Price forecasting for notebook computers 

    E-Print Network [OSTI]

    Rutherford, Derek Paul

    1997-01-01

    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...

  14. Multivariate Forecast Evaluation And Rationality Testing

    E-Print Network [OSTI]

    Komunjer, Ivana; OWYANG, MICHAEL

    2007-01-01

    Economy, 95(5), 1062—1088. MULTIVARIATE FORECASTS Chaudhuri,Notion of Quantiles for Multivariate Data,” Journal of thePress, United Kingdom. MULTIVARIATE FORECASTS Kirchgässner,

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

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

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

  16. Development and testing of improved statistical wind power forecasting methods.

    SciTech Connect (OSTI)

    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)

    2011-12-06

    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.

  17. jiliiil]iff(iiiiiJ ~ ~ ,,: "'-~I'~-

    E-Print Network [OSTI]

    Paraná, Universidade Federal do

    contribuindo com as discussões e sugerindo soluções que assegurem a democracia nas tomadas de decisão; IV

  18. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J.

    2011-02-23

    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.

  19. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    water heating systems, Heating Ventilating and Air Conditioning (HVAC) systems, wind speed predictions, control in power

  20. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01

    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.

  1. Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,

    E-Print Network [OSTI]

    Shenoy, Prashant

    Leveraging Weather Forecasts in Renewable Energy Systems Navin Sharmaa, , Jeremy Gummesonb , David, Binghamton, NY 13902 Abstract Systems that harvest environmental energy must carefully regulate their us- age to satisfy their demand. Regulating energy usage is challenging if a system's demands are not elastic, since

  2. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.

  3. Global disease monitoring and forecasting with Wikipedia

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: accessmore »logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.« less

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

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01

    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 ...

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

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

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

  6. Diagnosis of the Marine Low Cloud Simulation in the NCAR Community Earth System Model (CESM) and the NCEP Global Forecast System (GFS)-Modular Ocean Model v4 (MOM4) coupled model

    SciTech Connect (OSTI)

    Xiao, Heng; Mechoso, C. R.; Sun, Rui; Han, J.; Pan, H. L.; Park, S.; Hannay, Cecile; Bretherton, Christopher S.; Teixeira, J.

    2014-07-25

    We present a diagnostic analysis of the marine low cloud climatology simulated by two state-of-the-art coupled atmosphere-ocean models: the NCAR Community Earth System Model (CESM) and the NCEP Global Forecasting System (GFS). In both models, the shallow convection and boundary layer turbulence parameterizations have been recently updated: both models now use a mass-flux scheme for the parameterization of shallow convection, and a turbulence parameterization capable of handling Stratocumulus (Sc)-topped Planetary Boundary Layers (PBLs). For shallow convection, both models employ a convective trigger function based on the concept of convective inhibition and both include explicit convective overshooting/penetrative entrainment formulation. For Sc-topped PBL, both models treat explicitly turbulence mixing and cloud-top entrainment driven by cloud-top radiative cooling. Our focus is on the climatological transition from Sc to shallow Cumulus (Cu)-topped PBL in the subtropical eastern oceans. We show that in the CESM the coastal Sc-topped PBLs in the subtropical Eastern Pacific are well-simulated but the climatological transition from Sc to shallow Cu is too abrupt and happens too close to the coast. By contrast, in the GFS coupled simulation the coastal Sc amount and PBL depth are severely underestimated while the transition from Sc to shallow Cu is ³delayed² and offshore Sc cover is too extensive in the subtropical Eastern Pacific. We discuss the possible connections between such differences in the simulations and differences in the parameterizations of shallow convection and boundary layer turbulence in the two models.

  7. Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

    2012-09-01

    Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    weather prediction solar irradiance forecasts in the US.2013: Review of solar irradiance forecasting methods and asatellite-derived irradiances: Description and validation.

  9. Future Power Systems 20: The Smart Enterprise, its Objective...

    Energy Savers [EERE]

    0: The Smart Enterprise, its Objective and Forecasting. Future Power Systems 20: The Smart Enterprise, its Objective and Forecasting. Future Power Systems 20: The Smart Enterprise,...

  10. FORECASTING OF ATLANTIC TROPICAL CYCLONES USING A KILO-MEMBER ENSEMBLE

    E-Print Network [OSTI]

    Schubert, Wayne H.

    system using an efficient multigrid barotropic vorticity equation model (MBAR). Five perturbation classes Advisor Department Head ii #12;ABSTRACT OF THESIS FORECASTING OF ATLANTIC TROPICAL CYCLONES USING A KILO forecasts. These increases have been largely driven by improved numerical weather prediction models

  11. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)

    SciTech Connect (OSTI)

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

    2013-10-01

    This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

  12. Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization

    E-Print Network [OSTI]

    Nocedal, Jorge

    Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization M. Fisher J weather prediction centers to produce the initial conditions for 7- to 10-day weather fore- casts, with particular reference to the system in operation at the European Centre for Medium-Range Weather Forecasts. 1

  13. Management Forecast Quality and Capital Investment Decisions

    E-Print Network [OSTI]

    Goodman, Theodore H.

    Corporate investment decisions require managers to forecast expected future cash flows from potential investments. Although these forecasts are a critical component of successful investing, they are not directly observable ...

  14. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01

    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 ...

  15. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    FORECASTING THE ROLE OF RENEWABLES IN HAWAII Jayant SathayeFORECASTING THE ROLF OF RENEWABLES IN HAWAII J Sa and Henrythe Conservation Role of Renewables November 18, 1980 Page 2

  16. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    income 7 Figure 1.14: United States inflation Rate 8 Figure 1.15: Select United States interest Rates 8 2014 TABLE OF CONTENTS EXECUTiVE SUMMARY 1 CHAPTER 1: THE UNiTED STATES ECONOMY 3 Recent Trends Forecast Summary 2 CHAPTER 1: THE UNiTED STATES ECONOMY Figure 1.1: United States Real GDP Growth 3 Figure

  17. Modeling and Forecasting Electric Daily Peak Loads

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    for the same data. Two methods are described for forecasting daily peak loads up to one week ahead through, including generator unit commitment, hydro-thermal coordination, short-term maintenance, fuel allocation forecasting accuracies. STLF forecasting covers the daily peak load, total daily energy, and daily load curve

  18. Consensus Coal Production And Price Forecast For

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    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

  19. Forecasting phenology under global warming

    E-Print Network [OSTI]

    Silander Jr., John A.

    Forecasting phenology under global warming Ine´s Iba´n~ez1,*, Richard B. Primack2, Abraham J in phenology. Keywords: climate change; East Asia, global warming; growing season, hierarchical Bayes; plant is shifting, and these shifts have been linked to recent global warming (Parmesan & Yohe 2003; Root et al

  20. Utilize cloud computing to support dust storm forecasting Qunying Huanga

    E-Print Network [OSTI]

    Chen, Songqing

    storm forecasting operational system should support a disruptive fashion by scaling up to enable high to save energy and costs. With the capability of providing a large, elastic, and virtualized pool and property damages since 1995 (Figure 1). Deaths and injuries are usually caused by car accidents, because

  1. MET 416: TROPICAL ANALYSIS AND FORECASTING Spring Semester 2013

    E-Print Network [OSTI]

    current (nowcasting) and expected weather, using all available real-time operational weather data Exam 4/9 Summer trade-wind weather based on HaRP 4/11-16 Large-scale influences, Diurnal cycle to the development of tropical storm systems and mesoscale weather. Lectures will include a forecasting perspective

  2. A comparison study of data assimilation algorithms for ozone forecasts

    E-Print Network [OSTI]

    Mallet, Vivien

    A comparison study of data assimilation algorithms for ozone forecasts Lin Wu,1,2 V. Mallet,1,2 M assimilation schemes with the aim of designing suitable assimilation algorithms for short- range ozone but stable systems with high uncertainties (e.g., over 20% for ozone daily peaks (Hanna et al., 1998; Mallet

  3. Short-Term Solar Energy Forecasting Using Wireless Sensor Networks

    E-Print Network [OSTI]

    Cerpa, Alberto E.

    Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu an advantage for output power prediction. Solar Energy Prediction System Our prediction model is based variability of more then 100 kW per minute. For practical usage of solar energy, predicting times of high

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

    SciTech Connect (OSTI)

    Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

    2014-04-30

    This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.

  5. Forecasting wind speed financial return

    E-Print Network [OSTI]

    D'Amico, Guglielmo; Prattico, Flavio

    2013-01-01

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

  6. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16

    and encouragement. I am very grateful to Lucille and Michael Hobbs for their friendship, understanding and financial support. Finally, thank you to Tom Decker, Pat Jackson and Brian Zellar for all their contributions and hard work on this project... below: 1. Na?ve 2. Linear Regression 3. Moving Average 4. Exponential 5. Double exponential The na?ve forecasting method assumes that more recent data values are the best predictors of future values. The model is ? t+1 = Y t . Where ? t...

  7. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

    Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V.

    2011-11-29

    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.

  8. Using Climate Predictions in Great Lakes Hydrologic Forecasts T. E. Croley II1

    E-Print Network [OSTI]

    Lakes water levels cause extensive flooding, erosion, and damage to shorelines, shipping, and hydropower the forecasting system utility to decision makers and potential impacts in practical applications. CLIMATE EFFECTS

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

    SciTech Connect (OSTI)

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

    2013-05-01

    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.

  10. Weather Forecasts are for Wimps: Why Water Resource Managers Do Not Use Climate Forecasts

    E-Print Network [OSTI]

    Rayner, Steve; Lach, Denise; Ingram, Helen

    2005-01-01

    and Winter, S. G. : 1960, Weather Information and EconomicThe ENSO Signal 7, 4–6. WEATHER FORECASTS ARE FOR WIMPSWEATHER FORECASTS ARE FOR WIMPS ? : WHY WATER RESOURCE

  11. The Preservation of Physical Fashion Forecasts

    E-Print Network [OSTI]

    Kosztowny, Alexander John

    2015-01-01

    schools and their libraries, which use trend forecastingin archives and libraries would be that the trend forecastsin a library or archive, not exclusively to trend forecasts.

  12. Project Profile: Forecasting and Influencing Technological Progress...

    Energy Savers [EERE]

    R&D translates into improved performance and reduced costs for energy technologies. Motivation Technological forecasts, which plot the anticipated performance and costs of...

  13. Promotional forecasting in the grocery retail business

    E-Print Network [OSTI]

    Koottatep, Pakawkul

    2006-01-01

    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 ...

  14. Funding Opportunity Announcement for Wind Forecasting Improvement...

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

    that take place in complex terrain, this funding opportunity will improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

  15. Upcoming Funding Opportunity for Wind Forecasting Improvement...

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

    processes that take place in complex terrain, this funding would improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

  16. Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.

    2013-01-01

    Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

  17. Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power

    E-Print Network [OSTI]

    to the electricity price forecast. This resource mix is used to forecast the fuel consumption and carbon dioxide (CO2Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power Plan. This forecast is an estimate of the future price of electricity

  18. 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting

    E-Print Network [OSTI]

    Greenslade, Diana

    SHEET 6 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting and Warning Services The Bureau of Meteorology (the Bureau) is responsible for providing an effective flood forecasting and warning service in each Australian state

  19. Numerical Weather Forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L. [Westinghouse Savannah River Company, AIKEN, SC (United States)

    1998-11-01

    Weather forecasts at the Savannah River Site (SRS) are important for applications to emergency response. The fate of accidentally-released radiological materials and toxic chemicals can be determined by providing wind and turbulence input to atmospheric transport models. This operation has been routinely performed at SRS using the WIND System, a system of computer models and monitors which collect data from towers situated throughout the SRS. However, the information provided to these models is spatially homogeneous (in one or two dimensions) with an elementary forecasting capability. This paper discusses the use of an advanced three-dimensional prognostic numerical model to provide space and time-dependent meteorological data for use in the WIND System dispersion models. The extensive meteorological data collection at SRS serves as a ground truth for further model development as well as for use in other applications.

  20. Review of Variable Generation Forecasting in the West: July 2013 - March 2014

    SciTech Connect (OSTI)

    Widiss, R.; Porter, K.

    2014-03-01

    This report interviews 13 operating entities (OEs) in the Western Interconnection about their implementation of wind and solar forecasting. The report updates and expands upon one issued by NREL in 2012. As in the 2012 report, the OEs interviewed vary in size and character; the group includes independent system operators, balancing authorities, utilities, and other entities. Respondents' advice for other utilities includes starting sooner rather than later as it can take time to plan, prepare, and train a forecast; setting realistic expectations; using multiple forecasts; and incorporating several performance metrics.

  1. NREL: Transmission Grid Integration - Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines lightGeospatial ToolkitSMARTS -BeingFuture forForecasting NREL researchers

  2. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar2-0057-EA Jump to:ofEnia SpAFlex Fuels Energy JumpVyncke Jump to:Forecast

  3. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    Parsons, Simon

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc in demand forecasting for new communication services. Acknowledgments: The writing of this paper commenced employers or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica- tions

  4. Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting

    E-Print Network [OSTI]

    Plale, Beth

    Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting Nithya N. Vijayakumar {rramachandran, xli}@itsc.uah.edu Abstract-- Mesoscale meteorology forecasting as a data driven application Triggers, Data Mining, Stream Processing, Meteorology Forecasting I. INTRODUCTION Mesoscale meteorologists

  5. Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts

    E-Print Network [OSTI]

    Raftery, Adrian

    Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts VERONICA ensembles that generates calibrated probabilistic forecast products for weather quantities at indi- vidual perturbation (GOP) method, and extends BMA to generate calibrated probabilistic forecasts of whole weather

  6. 1360 IEEE Transactions on Power Systems, Vol. 12, No. 3, August 1997 Application of Fuzzy Logic Technology for Spatial Load Forecasting

    E-Print Network [OSTI]

    Chow, Mo-Yuen

    are required to provide reliable power to customers. In the design stages, utilities need to plan ahead-effective and reliable distribution system. In the design stages, utilities need to plan ahead for anticipated future in their territory. Therefore, utilities are very concerned about distribution planning. They would like to use

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind. Abstract-Short-term wind power forecasting is recognized nowadays as a major requirement for a secure and economic integration of wind power in a power system. In the case of large-scale integration, end users

  8. Nonparametric models for electricity load forecasting

    E-Print Network [OSTI]

    Genève, Université de

    Electricity consumption is constantly evolving due to changes in people habits, technological innovations1 Nonparametric models for electricity load forecasting JANUARY 23, 2015 Yannig Goude, Vincent at University Paris-Sud 11 Orsay. His research interests are electricity load forecasting, more generally time

  9. INTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev

    E-Print Network [OSTI]

    , discourse and semantic. They are based on a conceptual model underlying weather forecasts as well situations represented in the form of texts in NL, weather maps, data tables or combined information objectsINTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev I n s t i t u t e of Mathematics Acad

  10. Smooth Calibration, Leaky Forecasts, and Finite Recall

    E-Print Network [OSTI]

    Hart, Sergiu

    Smooth Calibration, Leaky Forecasts, and Finite Recall Sergiu Hart October 2015 SERGIU HART c 2015 ­ p. #12;Smooth Calibration, Leaky Forecasts, and Finite Recall Sergiu Hart Center for the Study of Rationality Dept of Mathematics Dept of Economics The Hebrew University of Jerusalem hart@huji.ac.il http://www.ma.huji.ac.il/hart

  11. Multivariate Time Series Forecasting in Incomplete Environments

    E-Print Network [OSTI]

    Roberts, Stephen

    Multivariate Time Series Forecasting in Incomplete Environments Technical Report PARG 08-03 Seung of Oxford December 2008 #12;Seung Min Lee and Stephen J. Roberts Technical Report PARG 08-03 Multivariate missing observations and forecasting future values in incomplete multivariate time series data. We study

  12. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author, Guangzhou 510301, China9 2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological10, China20 21 22 23 24 Submitted to Weather and Forecasting25 2014. 12. 2826 27 Corresponding author: Dr

  13. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Johnson, Richard H.

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author Fort Collins, Colorado7 October 20128 (submitted to Weather and Forecasting)9 1 Corresponding author address: Rebecca D. Adams-Selin, HQ Air Force Weather Agency 16th Weather Squadron, 101 Nelson Dr., Offutt

  14. The Wind Forecast Improvement Project (WFIP): A Public/Private...

    Office of Environmental Management (EM)

    The Wind Forecast Improvement Project (WFIP): A PublicPrivate Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The...

  15. Numerical weather forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L. [Westinghouse Savannah River Site, Aiken, SC (United States)

    1998-12-31

    Weather forecasts at the Savannah River Site (SRS) are important for applications to emergency response. The fate of accidentally released radiological materials and toxic chemicals can be determined by providing wind and turbulence input to atmospheric transport models. This operation has been routinely performed at SRS using the WIND system, a system of computer models and monitors that collects data from towers situated throughout the SRS. However, the information provided to these models is spatially homogeneous (in one or two dimensions) with an elementary forecasting capability. This paper discusses the use of an advanced three-dimensional prognostic numerical model to provide space- and time-dependent meteorological data for use in the WIND system dispersion models. The extensive meteorological data collection at SRS serves as a ground truth for further model development as well as for use in other applications. A prognostic mesoscale model, the regional atmospheric modeling system (RAMS), is used to provide these forecasts. Use of RAMS allows for incorporation of mesoscale features such as the sea breeze, which has been shown to affect local weather conditions. This paper discusses the mesoscale model and its configuration for the operational simulation, as well as an application using a dispersion model at the SRS.

  16. Short-term load forecasting using generalized regression and probabilistic neural networks in the electricity market

    SciTech Connect (OSTI)

    Tripathi, M.M.; Upadhyay, K.G.; Singh, S.N.

    2008-11-15

    For the economic and secure operation of power systems, a precise short-term load forecasting technique is essential. Modern load forecasting techniques - especially artificial neural network methods - are particularly attractive, as they have the ability to handle the non-linear relationships between load, weather temperature, and the factors affecting them directly. A test of two different ANN models on data from Australia's Victoria market is promising. (author)

  17. 526 VOLUME 14W E A T H E R A N D F O R E C A S T I N G Improved Accuracy in Severe Storm Forecasting by the Severe Local Storms Unit

    E-Print Network [OSTI]

    by the automation of largely clerical tasks, allowing the forecasters more time to focus on the forecast problem in Kansas City, numerous major changes took place in forecast products, computer systems, and personnel mi either side of a line from city A to city B). The watch process has played an important role over

  18. Earthquake Forecast via Neutrino Tomography

    E-Print Network [OSTI]

    Bin Wang; Ya-Zheng Chen; Xue-Qian Li

    2011-03-29

    We discuss the possibility of forecasting earthquakes by means of (anti)neutrino tomography. Antineutrinos emitted from reactors are used as a probe. As the antineutrinos traverse through a region prone to earthquakes, observable variations in the matter effect on the antineutrino oscillation would provide a tomography of the vicinity of the region. In this preliminary work, we adopt a simplified model for the geometrical profile and matter density in a fault zone. We calculate the survival probability of electron antineutrinos for cases without and with an anomalous accumulation of electrons which can be considered as a clear signal of the coming earthquake, at the geological region with a fault zone, and find that the variation may reach as much as 3% for $\\bar \

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

    SciTech Connect (OSTI)

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

    2013-11-01

    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.

  20. Forecasting Random Walks Under Drift Instability

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas

    will yield a biased forecast but will continue to have the least variance. On the other hand a forecast based on the sub-sample {yTi , yTi+1, . . . , yT }, where Ti > 1 is likely to have a lower bias but could be inefficient due to a higher variance... approach considered in Pesaran and Timmermann (2007) is to use different sub-windows to forecast and then average the outcomes, either by means of cross-validated weights or by simply using equal weights. To this end consider the sample {yTi , yTi+1...

  1. 1993 Solid Waste Reference Forecast Summary

    SciTech Connect (OSTI)

    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)

    1993-08-01

    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.

  2. Assessment of the possibility of forecasting future natural gas curtailments

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

    This study provides a preliminary assessment of the potential for determining probabilities of future natural-gas-supply interruptions by combining long-range weather forecasts and natural-gas supply/demand projections. An illustrative example which measures the probability of occurrence of heating-season natural-gas curtailments for industrial users in the southeastern US is analyzed. Based on the information on existing long-range weather forecasting techniques and natural gas supply/demand projections enumerated above, especially the high uncertainties involved in weather forecasting and the unavailability of adequate, reliable natural-gas projections that take account of seasonal weather variations and uncertainties in the nation's energy-economic system, it must be concluded that there is little possibility, at the present time, of combining the two to yield useful, believable probabilities of heating-season gas curtailments in a form useful for corporate and government decision makers and planners. Possible remedial actions are suggested that might render such data more useful for the desired purpose in the future. The task may simply require the adequate incorporation of uncertainty and seasonal weather trends into modeling systems and the courage to report projected data, so that realistic natural gas supply/demand scenarios and the probabilities of their occurrence will be available to decision makers during a time when such information is greatly needed.

  3. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

    Wind-Wave Probabilistic Forecasting based on Ensemble Predictions Maxime FORTIN Kongens Lyngby 2012.imm.dtu.dk IMM-PhD-2012-86 #12;Summary Wind and wave forecasts are of a crucial importance for a number weather forecasts and do not take any possible correlation into ac- count. Since wind and wave forecasts

  4. Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)

    SciTech Connect (OSTI)

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

    2013-10-01

    This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

  5. Dynamic Algorithm for Space Weather Forecasting System 

    E-Print Network [OSTI]

    Fischer, Luke D.

    2011-08-08

    .............................................................................................9 Task 1: Developing a database of solar weather data ...............................9 Task 2: Developing the ?dynamic analysis? process .............................. 10 Task 3: Developing a Java applet that presents real-time solar...-computing resources have been recently discovered. Software materials include the programming language ?Java?, the Graphical-User-Interface ?JCreator?, and Rapid Miner. We also make use of publicly available scientific databases that contain a vast plethora...

  6. STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 Mignon Marks Principal Author Mignon Marks Project Manager David Ashuckian Manager ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY DIVISION B.B. Blevins Executive Director

  7. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  8. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  9. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    /demographic growth, relatively low electricity and natural gas rates, and relatively low efficiency program CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity Manager Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY

  10. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P. Oglesby Executive

  11. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    high economic/demographic growth, relatively low electricity and natural gas rates, and relatively low CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION

  12. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  13. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand Gough Office Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  14. Text-Alternative Version LED Lighting Forecast

    Broader source: Energy.gov [DOE]

    The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications estimates the energy savings of LED white-light sources over the analysis period of 2013 to 2030....

  15. Load Forecast For use in Resource Adequacy

    E-Print Network [OSTI]

    forecast of 4) Calculate Hourly Load Allocation Factor s for each day for 2019 For use in RA analysis as a function ofthe load for electricity in the region as a function of cyclical, weather and economic variables

  16. Testing Competing High-Resolution Precipitation Forecasts

    E-Print Network [OSTI]

    Gilleland, Eric

    Testing Competing High-Resolution Precipitation Forecasts Eric Gilleland Research Prediction Comparison Test D1 D2 D = D1 ­ D2 copyright NCAR 2013 Loss Differential Field #12;Spatial Prediction Comparison Test Introduced by Hering and Genton

  17. New product forecasting in volatile markets

    E-Print Network [OSTI]

    Baldwin, Alexander (Alexander Lee)

    2014-01-01

    Forecasting demand for limited-life cycle products is essentially projecting an arc trend of demand growth and decline over a relatively short time horizon. When planning for a new limited-life product, many marketing and ...

  18. Potential Economic Value of Seasonal Hurricane Forecasts

    E-Print Network [OSTI]

    Emanuel, Kerry Andrew

    This paper explores the potential utility of seasonal Atlantic hurricane forecasts to a hypothetical property insurance firm whose insured properties are broadly distributed along the U.S. Gulf and East Coasts. Using a ...

  19. 13.2 A REPORT AND FEATURE-BASED VERIFICATION STUDY OF THE CAPS 2008 STORM-SCALE ENSEMBLE FORECASTS FOR SEVERE CONVECTIVE WEATHER

    E-Print Network [OSTI]

    of computing power, innovative numerical systems, and assimilation of observations at high spatial and temporal system as a means by which model error and uncertainty can be quantified in the forecast. Employing13.2 A REPORT AND FEATURE-BASED VERIFICATION STUDY OF THE CAPS 2008 STORM-SCALE ENSEMBLE FORECASTS

  20. Intra-hour Direct Normal Irradiance solar forecasting using genetic programming

    E-Print Network [OSTI]

    Queener, Benjamin Daniel

    2012-01-01

    guideline for Solar Power Forecasting Performance . . 46 viof forecasting techniques for solar power production with noand A. Pavlovski, “Solar power forecasting performance

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of the WRF model solar irradiance forecasts in Andalusia (Beyer, H. , 2009.    Irradiance forecasting for the power dependent probabilistic irradiance  forecasts for coastal 

  2. Mathematics Of Ice To Aid Global Warming Forecasts Mathematics Of Ice To Aid Global Warming Forecasts

    E-Print Network [OSTI]

    Golden, Kenneth M.

    Mathematics Of Ice To Aid Global Warming Forecasts Mathematics Of Ice To Aid Global Warming forecasts of how global warming will affect polar icepacks. See also: Earth & Climate q Global Warming q the effects of climate warming, and its presence greatly reduces solar heating of the polar oceans." "Sea ice

  3. Forecasting Prices andForecasting Prices and Congestion forCongestion for

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    Goal: Design nodal price and grid congestion forecasting tools for market operators and market Traders To facilitate scenario-conditioned planning Price forecasting for Market Participants (MPs) To manage short for portfolio management by power market participants Conclusion #12;Project OverviewProject Overview Project

  4. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

    Templeton, K.J.; Clary, J.L.

    1994-09-01

    This report describes a 30-year forecast of the solid waste volumes by container type. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste. These volumes and their associated container types will be generated or received at the US Department of Energy Hanford Site for storage, treatment, and disposal at Westinghouse Hanford Company`s Solid Waste Operations Complex (SWOC) during a 30-year period from FY 1994 through FY 2023. The forecast data for the 30-year period indicates that approximately 307,150 m{sup 3} of LLMW and TRU/TRUM waste will be managed by the SWOC. The main container type for this waste is 55-gallon drums, which will be used to ship 36% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of 55-gallon drums is Past Practice Remediation. This waste will be generated by the Environmental Restoration Program during remediation of Hanford`s past practice sites. Although Past Practice Remediation is the primary generator of 55-gallon drums, most waste generators are planning to ship some percentage of their waste in 55-gallon drums. Long-length equipment containers (LECs) are forecasted to contain 32% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of LECs is the Long-Length Equipment waste generator, which is responsible for retrieving contaminated long-length equipment from the tank farms. Boxes are forecasted to contain 21% of the waste. These containers are primarily forecasted for use by the Environmental Restoration Operations--D&D of Surplus Facilities waste generator. This waste generator is responsible for the solid waste generated during decontamination and decommissioning (D&D) of the facilities currently on the Surplus Facilities Program Plan. The remaining LLMW and TRU/TRUM waste volume is planned to be shipped in casks and other miscellaneous containers.

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

    Reports and Publications (EIA)

    1998-01-01

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

  6. Load Pocket Forecasting Software E. A. Feinberg, D. Genethliou, J.T. Hajagos, B.G. Irrgang, and R. J. Rossin

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    by electric utilities to estimate and forecast the load growth in different service areas. The software builds. The software can be used for area planning purposes. The software contains user's tools to design new load pockets and to modify the existing ones. Index Terms--Load forecasting, power system planning I

  7. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output Perturbation

    E-Print Network [OSTI]

    Raftery, Adrian

    Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output. This is typically not feasible for mesoscale weather prediction carried out locally by organizations without by simulating realizations of the geostatistical model. The method is applied to 48-hour mesoscale forecasts

  8. New directions for forecasting air travel passenger demand

    E-Print Network [OSTI]

    Garvett, Donald Stephen

    1974-01-01

    While few will disagree that sound forecasts are an essential prerequisite to rational transportation planning and analysis, the making of these forecasts has become a complex problem with the broadening of the scope and ...

  9. Generalized Cost Function Based Forecasting for Periodically Measured Nonstationary Traffic

    E-Print Network [OSTI]

    Zeng, Yong - Department of Mathematics and Statistics, University of Missouri

    1 Generalized Cost Function Based Forecasting for Periodically Measured Nonstationary Traffic true value. However, such a forecast- ing function is not directly applicable for applications potentially result in insufficient allocation of bandwidth leading to short term data loss. To facilitate

  10. The effect of multinationality on management earnings forecasts 

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29

    This study examines the relationship between a firm??s degree of multinationality and its managers?? earnings forecasts. Firms with a high degree of multinationality are subject to greater uncertainty regarding earnings forecasts due...

  11. Market perceptions of efficiency and news in analyst forecast errors 

    E-Print Network [OSTI]

    Chevis, Gia Marie

    2004-11-15

    Financial analysts are considered inefficient when they do not fully incorporate relevant information into their forecasts. In this dissertation, I investigate differences in the observable efficiency of analysts' earnings forecasts between firms...

  12. DOE Releases Latest Report on Energy Savings Forecast of Solid...

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

    Latest Report on Energy Savings Forecast of Solid-State Lighting DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting September 12, 2014 - 2:06pm Addthis...

  13. U.S. Regional Demand Forecasts Using NEMS and GIS

    E-Print Network [OSTI]

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

    2005-01-01

    Forecasts Using NEMS and GIS National Climatic Data Center.with Changing Boundaries." Use of GIS to Understand Socio-Forecasts Using NEMS and GIS Appendix A. Map Results Gallery

  14. OPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization

    E-Print Network [OSTI]

    .................................................................................................................................... 323 II. SCIENCE OF EARTHQUAKE FORECASTING AND PREDICTION 325 A. Definitions and Concepts....................................................................................................................................... 325 B. Research on Earthquake PredictabilityOPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization Report

  15. AVLIS: a technical and economic forecast

    SciTech Connect (OSTI)

    Davis, J.I.; Spaeth, M.L.

    1986-01-01

    The AVLIS process has intrinsically large isotopic selectivity and hence high separative capacity per module. The critical components essential to achieving the high production rates represent a small fraction (approx.10%) of the total capital cost of a production facility, and the reference production designs are based on frequent replacement of these components. The specifications for replacement frequencies in a plant are conservative with respect to our expectations; it is reasonable to expect that, as the plant is operated, the specifications will be exceeded and production costs will continue to fall. Major improvements in separator production rates and laser system efficiencies (approx.power) are expected to occur as a natural evolution in component improvements. With respect to the reference design, such improvements have only marginal economic value, but given the exigencies of moving from engineering demonstration to production operations, we continue to pursue these improvements in order to offset any unforeseen cost increases. Thus, our technical and economic forecasts for the AVLIS process remain very positive. The near-term challenge is to obtain stable funding and a commitment to bring the process to full production conditions within the next five years. If the funding and commitment are not maintained, the team will disperse and the know-how will be lost before it can be translated into production operations. The motivation to preserve the option for low-cost AVLIS SWU production is integrally tied to the motivation to maintain a competitive nuclear option. The US industry can certainly survive without AVLIS, but our tradition as technology leader in the industry will certainly be lost.

  16. Wind power forecasting in U.S. electricity markets.

    SciTech Connect (OSTI)

    Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

    2010-04-01

    Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

  17. Wind power forecasting in U.S. Electricity markets

    SciTech Connect (OSTI)

    Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

    2010-04-15

    Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

  18. Managerial Career Concerns and Earnings Forecasts SARAH SHAIKH

    E-Print Network [OSTI]

    Tipple, Brett

    's aversion to risk, I find that a CEO is less likely to issue an earnings forecast in periods of stricter non is more pronounced for a CEO who has greater concern for his reputation, faces more risk in forecasting the provision of earnings forecasts. Literature has long recognized that the labor market provides distinct

  19. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    McBurney, Peter

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc to redress this situation by presenting a discussion of the issues involved in demand forecasting for new or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica­ tions Services. 1 #12

  20. Neural Network forecasts of the tropical Pacific sea surface temperatures

    E-Print Network [OSTI]

    Hsieh, William

    Neural Network forecasts of the tropical Pacific sea surface temperatures Aiming Wu, William W Tang Jet Propulsion Laboratory, Pasadena, CA, USA Neural Networks (in press) December 11, 2005 title: Forecast of sea surface temperature 1 #12;Neural Network forecasts of the tropical Pacific sea

  1. Managing Wind Power Forecast Uncertainty in Electric Brandon Keith Mauch

    E-Print Network [OSTI]

    i Managing Wind Power Forecast Uncertainty in Electric Grids Brandon Keith Mauch Co Paulina Jaramillo Doctor Paul Fischbeck 2012 #12;ii #12;iii Managing Wind Power Forecast Uncertainty generated from wind power is both variable and uncertain. Wind forecasts provide valuable information

  2. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

    Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power. This paper presents two methods focusing on forecasting large and sharp variations in power output of a wind

  3. Choosing Words in Computer-Generated Weather Forecasts

    E-Print Network [OSTI]

    Reiter, Ehud

    to communicate numeric weather data. A corpus-based analysis of how humans write forecasts showed that there wereTime- Mousam weather-forecast generator to use consistent data-to-word rules, which avoided words which were weather forecast texts from numerical weather pre- diction data (SumTime-Mousam in fact is used

  4. Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging J. MCLEAN 2011, in final form 26 May 2012) ABSTRACT Probabilistic forecasts of wind vectors are becoming critical with univariate quantities, statistical approaches to wind vector forecasting must be based on bivariate

  5. Accuracy of near real time updates in wind power forecasting

    E-Print Network [OSTI]

    Heinemann, Detlev

    Accuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method #12;EMS/ECAM 2007 ­ Nadja Saleck Wind power forecast data observed wind power input (2004 ­ 2006

  6. Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc in the context of wind power, where under- forecasting and overforecasting carry different financial penal- ties, calibrated and sharp probabilistic forecasts can help to make wind power a more financially competitive alter

  7. Forecasting Building Occupancy Using Sensor Network James Howard

    E-Print Network [OSTI]

    Hoff, William A.

    Forecasting Building Occupancy Using Sensor Network Data James Howard Colorado School of Mines@mines.edu ABSTRACT Forecasting the occupancy of buildings can lead to signif- icant improvement of smart heating throughout a building, we perform data mining to forecast occupancy a short time (i.e., up to 60 minutes

  8. Weather Forecasting -Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting - Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, "weather forecasts" are created such that selected wireless LAN performance indicators might be used to evaluate the effec- tiveness of individual weather forecasts. The paper evaluates six distinct weather

  9. Weather Forecasting Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting ­ Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, ``weather forecasts'' are created such that selected wireless LAN performance indicators might be used to evaluate the e#ec­ tiveness of individual weather forecasts. The paper evaluates six distinct weather

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

    E-Print Network [OSTI]

    Povinelli, Richard J.

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

  11. Preprints, 15th AMS Conference on Weather Analysis and Forecasting

    E-Print Network [OSTI]

    Doswell III, Charles A.

    ) models have substantially improved forecast skill. Recent and planned changes along these lines (e to delivering two kinds of weather products. The first is a day-to-day forecast of weather elements, e by the private sector. Improvements in automated techniques for the forecasting of basic weather elements

  12. Influences of soil moisture and vegetation on convective precipitation forecasts

    E-Print Network [OSTI]

    Robock, Alan

    Influences of soil moisture and vegetation on convective precipitation forecasts over the United and vegetation on 30 h convective precipitation forecasts using the Weather Research and Forecasting model over, the complete removal of vegetation produced substantially less precipitation, while conversion to forest led

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    of Solar 2011, American Solar Energy Society, Raleigh, NC.Description and validation. Solar Energy, 73 (5), 307-317.forecast database. Solar Energy, Perez, R. , S. Kivalov, J.

  14. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

    This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

  15. Forecasting Hot Water Consumption in Residential Houses

    E-Print Network [OSTI]

    MacDonald, Mark

    and technological advancement in energy-intensive applications are causing fast electric energy consumption growth and consumption of electricity [8], as long as there is no significant correlation between intermittent energyArticle Forecasting Hot Water Consumption in Residential Houses Linas Gelazanskas * and Kelum A

  16. GENETIC ALGORITHM FORECASTING FOR TELECOMMUNICATIONS PRODUCTS

    E-Print Network [OSTI]

    Havlicek, Joebob

    available economic indicators such as Disposable Personal Income and New Housing Starts as independent exhibiting maximal fitness achieved RMS forecast errors below the the average two-week sales figure. 1 (Holland, 1975), (Packard, 1990), (Koza, 1992), (Bäck, et al., 1997), (Mitchell, 1998). For example, Meyer

  17. GOES Aviation Products Aviation Weather Forecasting

    E-Print Network [OSTI]

    Kuligowski, Bob

    GOES Aviation Products · The GOES aviation forecast products are based on energy measured in different characteristics #12;GOES Aviation Products Quiz · What is a geostationary satellite? · What generates energy received by the satellite in the visible band? · What generates energy received by the satellite

  18. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Reiter, Ehud

    summarisation. We found three alternative ways in which we could model data summarisation. One approach is based turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from

  19. "FLIGHT PLAN" FORECASTS SEATTLE/TACOMA AND

    E-Print Network [OSTI]

    ASSESSMENT OF THE "FLIGHT PLAN" FORECASTS FOR SEATTLE/TACOMA AND REGIONAL AIRPORTS TOGETHER 1. Introduction 5 2. Airport Planning Process 7 Traditional Master Planning Application to Seattle/Tacoma. Uncertainty about Capacity 27 A Fuzzy Concept Assessment Factors Application to Seattle/Tacoma 7. Assessment

  20. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27

    This paper presents a nonparametric diffusion modeling approach for forecasting partially observed noisy turbulent modes. The proposed forecast model uses a basis of smooth functions (constructed with the diffusion maps algorithm) to represent probability densities, so that the forecast model becomes a linear map in this basis. We estimate this linear map by exploiting a previously established rigorous connection between the discrete time shift map and the semi-group solution associated to the backward Kolmogorov equation. In order to smooth the noisy data, we apply diffusion maps to a delay embedding of the noisy data, which also helps to account for the interactions between the observed and unobserved modes. We show that this delay embedding biases the geometry of the data in a way which extracts the most predictable component of the dynamics. The resulting model approximates the semigroup solutions of the generator of the underlying dynamics in the limit of large data and in the observation noise limit. We will show numerical examples on a wide-range of well-studied turbulent modes, including the Fourier modes of the energy conserving Truncated Burgers-Hopf (TBH) model, the Lorenz-96 model in weakly chaotic to fully turbulent regimes, and the barotropic modes of a quasi-geostrophic model with baroclinic instabilities. In these examples, forecasting skills of the nonparametric diffusion model are compared to a wide-range of stochastic parametric modeling approaches, which account for the nonlinear interactions between the observed and unobserved modes with white and colored noises.

  1. Stochastic Weather Generator Based Ensemble Streamflow Forecasting

    E-Print Network [OSTI]

    Stochastic Weather Generator Based Ensemble Streamflow Forecasting by Nina Marie Caraway B of Civil Engineering 2012 #12;This thesis entitled: Stochastic Weather Generator Based Ensemble Streamflow mentioned discipline. #12;iii Caraway, Nina Marie (M.S., Civil Engineering) Stochastic Weather Generator

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

    SciTech Connect (OSTI)

    Michalakes, J.; Chen, S.; Dudhia, J.; Hart, L.; Klemp, J.; Middlecoff, J.; Skamarock, W.

    2001-02-05

    The Weather Research and Forecast (WRF) project is a multi-institutional effort to develop an advanced mesoscale forecast and data assimilation system that is accurate, efficient, and scalable across a range of scales and over a host of computer platforms. The first release, WRF 1.0, was November 30, 2000, with operational deployment targeted for the 2004-05 time frame. This paper provides an overview of the project and current status of the WRF development effort in the areas of numerics and physics, software and data architecture, and single-source parallelism and performance portability.

  3. Load Forecasting of Supermarket Refrigeration

    E-Print Network [OSTI]

    @compute.dtu.dk www.compute.dtu.dk M.Sc.-2013-87 #12;Summary (English) The Danish power production coming from energy system. Observed refrigeration load and local ambient temperature from a Danish su- permarket renewable energy, is increasing, therefore a flexible energy system is needed. In the present Thesis

  4. A 110-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe Floods of 200307*

    E-Print Network [OSTI]

    Webster, Peter J.

    A 1­10-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe of the Brahmaputra and Ganges Rivers as they flow into Bangladesh; it has been operational since 2003. The Bangladesh points of the Ganges and Brahmaputra into Bangladesh. Forecasts with 1­10-day horizons are presented

  5. Forecastability as a Design Criterion in Wind Resource Assessment: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

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

  6. Bidding wind energy exploiting wind speed forecasts Antonio Giannitrapani, Simone Paoletti,

    E-Print Network [OSTI]

    Garulli, Andrea

    -ahead generation profile for a wind power producer by exploiting wind speed forecasts provided by a meteorological service. In the con- sidered framework, the wind power producer is called to take part integration in the grid is causing serious problems to transmission and distribution system operators [2]. One

  7. SHORT-TERM FORECASTING OF SOLAR RADIATION BASED ON SATELLITE DATA WITH STATISTICAL METHODS

    E-Print Network [OSTI]

    Heinemann, Detlev

    for this systems. Depending on the application, prediction of solar irradiance is beneficial on different timeSHORT-TERM FORECASTING OF SOLAR RADIATION BASED ON SATELLITE DATA WITH STATISTICAL METHODS Annette Solar World Congress. This portion of the paper is the abstract. The abstract should not exceed 250

  8. European Wind Energy Conference -Brussels, Belgium, April 2008 Data mining for wind power forecasting

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    European Wind Energy Conference - Brussels, Belgium, April 2008 Data mining for wind power-term forecasting of wind energy produc- tion up to 2-3 days ahead is recognized as a major contribution the improvement of predic- tion systems performance is recognised as one of the priorities in wind energy research

  9. Evalua&ng the usefulness of spa&al forecast verifica&on methods for

    E-Print Network [OSTI]

    Gilleland, Eric

    Evalua&ng the usefulness of spa&al forecast verifica&on methods for developing op&mal mix of observa&onal systems and NWP for real-&me nowcas&ng and forecas&ng&al end users Developing a Quan.ta.ve Precipita.on Es.ma.on, Nowcas.ng and Streamflow

  10. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

    SciTech Connect (OSTI)

    Brown, C. W.; Hood, Raleigh R.; Long, Wen; Jacobs, John M.; Ramers, D. L.; Wazniak, C.; Wiggert, J. D.; Wood, R.; Xu, J.

    2013-09-01

    The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat models of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanistic–empirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.

  11. Testing Automated Solar Flare Forecasting With 13 Years of MDI Synoptic Magnetograms

    E-Print Network [OSTI]

    Hoeksema, Todd

    becomes more technologically dependent on complex global systems, the potential risk posedTesting Automated Solar Flare Forecasting With 13 Years of MDI Synoptic Magnetograms J.P. Mason1 is statistically associated with changes in several characteris- tics of the line-of-sight magnetic field in solar

  12. IEEE TRANSACTIONS ON POWER SYSTEMS 1 Economic Impact of Electricity Market Price

    E-Print Network [OSTI]

    Cañizares, Claudio A.

    IEEE TRANSACTIONS ON POWER SYSTEMS 1 Economic Impact of Electricity Market Price Forecasting Errors to forecast electricity market prices and improve forecast accuracy. However, no studies have been reported, the application of electricity market price forecasts to short-term operation scheduling of two typical

  13. Combinatorial Evolution and Forecasting of Communication Protocol ZigBee

    E-Print Network [OSTI]

    Levin, Mark Sh; Kistler, Rolf; Klapproth, Alexander

    2012-01-01

    The article addresses combinatorial evolution and forecasting of communication protocol for wireless sensor networks (ZigBee). Morphological tree structure (a version of and-or tree) is used as a hierarchical model for the protocol. Three generations of ZigBee protocol are examined. A set of protocol change operations is generated and described. The change operations are used as items for forecasting based on combinatorial problems (e.g., clustering, knapsack problem, multiple choice knapsack problem). Two kinds of preliminary forecasts for the examined communication protocol are considered: (i) direct expert (expert judgment) based forecast, (ii) computation of the forecast(s) (usage of multicriteria decision making and combinatorial optimization problems). Finally, aggregation of the obtained preliminary forecasts is considered (two aggregation strategies are used).

  14. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs: FORECASTING EARTH'S SURFACE RESPONSE

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Pelletier, Jon D.; Brad Murray, A.; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; et al

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we havemore »the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.« less

  15. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

    Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

    2014-12-30

    A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

  16. Two techniques for forecasting clear air turbulence 

    E-Print Network [OSTI]

    Arbeiter, Randolph George

    1977-01-01

    result in only mild annoyance or discomfort (air sickness) to crew and passengers. As it becomes moderate, difficulty may be experienced in moving about inside the airplane and the crew may momentarily lose control. Severe CAT can result in injury... successfully used by the Air Force Clobal Heather Central (Barnett, 1970) for oper" tional forecasting on a day-to-day basis. Furthermore, its usefulness 1' or supersonic aircraft in the stratosphere v;as successfully demonstrated by Scoggins et H. (1975...

  17. Solar Wind Forecasting with Coronal Holes

    E-Print Network [OSTI]

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

    2007-01-09

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

  18. Using Wikipedia to forecast disease

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentric viewing system for light collectionEnergy

  19. LANL JOWOG 31 2012 Forecast

    SciTech Connect (OSTI)

    Vidlak, Anton J. II [Los Alamos National Laboratory

    2012-08-08

    Joint Working Group (JOWOG) 31, Nuclear Weapons Engineering, has a particularly broad scope of activities within its charter which emphasizes systems engineering. JOWOG 31 brings together experts from AWE and the national laboratories to address engineering issues associated with warhead design and certification. Some of the key areas of interaction, as addressed by the HOCWOGs are: (1) Engineering Analysis, (2) Hydrodynamic Testing, (3) Environmental Testing, and (4) Model Based Integrated Toolkit (MBIT). Gas Transfer Systems and Condition Monitoring interaction has been moved back to JOWOG 31. The regularly scheduled JOWOG 31 activities are the General Sessions, Executive Sessions, Focused Exchanges and HOCWOGs. General Sessions are scheduled every 12-18 months and are supported by the four design laboratories (AWE, LANL, LLNL, and SNL). Beneficial in educating the next generation of weapons engineers and establishing contacts between AWE and the US laboratory personnel. General Sessions are based on a blend of presentations and workshops centered on various themed subjects directly related to Stockpile Stewardship. HOCWOG meetings are more narrowly focused than the General Sessions. They feature presentations by experts in the field with a greater emphasis on round table discussions. Typically about 20 people attend. Focused exchanges are generally the result of interactions within JOWOG general sessions or HOCWOG meetings. They generally span a very specific topic of current interest within the US and UK.

  20. The Commission Forecast 1992 Report: Important Resource Planning Issues 

    E-Print Network [OSTI]

    Adib, P.

    1992-01-01

    FORECAST 1992 REPORT: IMPORTANT RESOURCE PLANNING ISSUES PARVIZ ADIB MANAGER, ECONOMIC ANALYSIS SECTION ELECTRIC DIVISION PUBLIC UTILITY COMMISSION OF TEXAS ABSTRACT There is a general agreement among experts in the electric utility industry... there are many important issues in the preparation of a utility's electric resource plan, the Commission staff will address a few important ones in the next Commission Forecast Report (Forecast '92). In particular, the Commission staff will insure...

  1. The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01

    function. The forecasts of oil, coal and gas prices as wellforecasts for natural gas consumption, electricity sales, coal and electricity prices,

  2. Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures

    E-Print Network [OSTI]

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

    2011-01-01

    Forecasting Dangerous Inmate Misconduct: An Applications ofof Term Length more dangerous than other inmates servingIV beds or moving less dangerous Level IV inmates to Level

  3. Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures

    E-Print Network [OSTI]

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

    2005-01-01

    Forecasting Dangerous Inmate Misconduct: An Applications ofof Term Length more dangerous than other inmates servingIV beds or moving less dangerous Level IV inmates to Level

  4. Ramping Effect on Forecast Use: Integrated Ramping (Presentation...

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

    the shift from ramping. * the benefits - better use of forecast values (load or net load) - reduce the amount of variability that the regulation reserve must accommodate...

  5. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

    SciTech Connect (OSTI)

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-12-08

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  6. Weather-based yield forecasts developed for 12 California crops

    E-Print Network [OSTI]

    Lobell, David; Cahill, Kimberly Nicholas; Field, Christopher

    2006-01-01

    RESEARCH ARTICLE Weather-based yield forecasts developed fordepend largely on the weather, measurements from existingpredictions. We developed weather-based models of statewide

  7. Nuclear Theory Helps Forecast Neutron Star Temperatures | U.S...

    Office of Science (SC) Website

    Nuclear Theory Helps Forecast Neutron Star Temperatures Nuclear Physics (NP) NP Home About Research Facilities Science Highlights Benefits of NP Funding Opportunities Nuclear...

  8. EIA lowers forecast for summer gasoline prices

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural GasNatural GasEIA lowers forecast for summer gasoline prices

  9. Motivation Methods Model configuration Results Forecasting Summary & Outlook Retrieving direct and diffuse radiation with the

    E-Print Network [OSTI]

    Heinemann, Detlev

    Motivation Methods Model configuration Results Forecasting Summary & Outlook 1/ 14 Retrieving. 17, 2015 #12;Motivation Methods Model configuration Results Forecasting Summary & Outlook 2/ 14 Motivation Sky Imager based shortest-term solar irradiance forecasts for local solar energy applications

  10. ECMWF analyses and forecasts of 500 mb synoptic-scale activity during wintertime blocking 

    E-Print Network [OSTI]

    Matson, David Michael

    1993-01-01

    An observational study of 500 mb atmospheric blocking is conducted based on an European Centre for Medium-Range Weather Forecasts (ECMWF) wintertime analysis and forecast dataset during dynamic extended range forecasting ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

    revisions to the EIA’s natural gas price forecasts in AEOsolely on the AEO 2005 natural gas price forecasts willComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

  12. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

    to estimate the base-case natural gas price forecast, but toComparison of AEO 2010 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

  13. Reducing the demand forecast error due to the bullwhip effect in the computer processor industry

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01

    Intel's current demand-forecasting processes rely on customers' demand forecasts. Customers do not revise demand forecasts as demand decreases until the last minute. Intel's current demand models provide little guidance ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

    revisions to the EIA’s natural gas price forecasts in AEOon the AEO 2005 natural gas price forecasts will likely onceComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

  15. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

    to estimate the base-case natural gas price forecast, but toComparison of AEO 2010 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from the AEO

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

    E-Print Network [OSTI]

    Jamieson, Bruce

    HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson and decision makers strongly rely on Numerical Weather Prediction (NWP) models, for example on the forecasted on forecasted precipitation. KEYWORDS: Numerical weather prediction models, validation, precipitation 1

  17. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01

    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.

  18. Revised 1997 Retail Electricity Price Forecast Principal Author: Ben Arikawa

    E-Print Network [OSTI]

    Revised 1997 Retail Electricity Price Forecast March 1998 Principal Author: Ben Arikawa Electricity 1997 FORE08.DOC Page 1 CALIFORNIA ENERGY COMMISSION ELECTRICITY ANALYSIS OFFICE REVISED 1997 RETAIL ELECTRICITY PRICE FORECAST Introduction The Electricity Analysis Office of the California Energy Commission

  19. Impact of PV forecasts uncertainty in batteries management in microgrids

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Impact of PV forecasts uncertainty in batteries management in microgrids Andrea Michiorri Arthur-based battery schedule optimisation in microgrids in presence of network constraints. We examine a specific case production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size

  20. Forecasting Hot Water Consumption in Dwellings Using Artifitial Neural Networks

    E-Print Network [OSTI]

    MacDonald, Mark

    electricity consumption in time. This paper investigates the ability on Artificial Neural Networks to predict shift electric energy. Keywords--Hot Water Consumption; Forecasting; Artifitial Neural Networks; SmartForecasting Hot Water Consumption in Dwellings Using Artifitial Neural Networks Linas Gelazanskas

  1. Draft for Public Comment Appendix A. Demand Forecast

    E-Print Network [OSTI]

    in the forecast of electricity consumption for those years has been less than one half of a percent. Figure A-1 forecast of electricity demand is a required component of the Council's Northwest Regional Conservation and Electric Power Plan.1 Understanding growth in electricity demand is, of course, crucial to determining

  2. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    of transportation fuel and crude oil import requirements. The transportation energy demand forecasts make. The transportation fuel and crude oil import requirement assessments build on assumptions about California crude oil forecasts, transportation energy, gasoline, diesel, jet fuel, crude oil production, fuel imports, crude oil

  3. A Deep Hybrid Model for Weather Forecasting Aditya Grover

    E-Print Network [OSTI]

    Horvitz, Eric

    @microsoft.com ABSTRACT Weather forecasting is a canonical predictive challenge that has depended primarily on model-based methods. We ex- plore new directions with forecasting weather as a data- intensive challenge that involves the joint statistics of a set of weather-related vari- ables. We show how the base model can be enhanced

  4. Hydrological Forecasting Improvements Primary Investigator: Thomas Croley -NOAA GLERL (Emeritus)

    E-Print Network [OSTI]

    multiple data streams in a near-real-time manner and incorporate them into the AHPS data base, run for matching weather forecasts with historical data, and prepare extensive forecasts of hydrology probabilities maximum use of all available information and be based on efficient and true hydrological process models

  5. DEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA)

    E-Print Network [OSTI]

    in a data base and graphic representation with tile standard meteorological icons on a map, e.g. iconsDEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA) by BENGT SIGURD, Sweden E-mail: linglund@gemini.ldc.lu.se FAX:46-(0)46 104210 Introduction and abstract Weather forecasts

  6. Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    markets could aid in the design of appropriate price forecasting tools for such markets. Scenario1 Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets Qun Zhou, restructured wholesale power markets, scenario generation, ARMA model, moment-matching method I. INTRODUCTION

  7. Probabilistic forecasting of solar flares from vector magnetogram data

    E-Print Network [OSTI]

    Barnes, Graham

    Probabilistic forecasting of solar flares from vector magnetogram data G. Barnes,1 K. D. Leka,1 E to solar flare forecasting, adapted to provide the probability that a measurement belongs to either group, the groups in this case being solar active regions which produced a flare within 24 hours and those

  8. Human Trajectory Forecasting In Indoor Environments Using Geometric Context

    E-Print Network [OSTI]

    . In addressing this problem, we have built a model to estimate the occupancy behavior of humans based enhancement in the accuracy of trajectory forecasting by incorporating the occupancy behavior model. Keywords Trajectory forecasting, human occupancy behavior, 3D ge- ometric context 1. INTRODUCTION Given a human

  9. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    . Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data Office. Andrea Gough ran the summary energy model and supervised data preparation. Glen Sharp prepared models. Both the staff revised energy consumption and peak forecasts are slightly higher than

  10. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

    E-Print Network [OSTI]

    Washington at Seattle, University of

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

  11. MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF

    E-Print Network [OSTI]

    MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF CLOUD COVER AND WATER VAPOUR Purchase Order 58311/ODG/99/8362/GWI/LET #12;i PREFACE Starting in August 1998, operational forecasts satellite imagery from the Co-operative Institute for Research in the Atmosphere (CIRA) and upper

  12. Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids

    E-Print Network [OSTI]

    Hwang, Kai

    1 Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids Yogesh Simmhan. One of the characteristic applications of Smart Grids is demand response optimization (DR). The goal of DR is to use the power consumption time series data to reliable forecast the future consumption

  13. THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD

    E-Print Network [OSTI]

    THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD ENERGY SERVICES by Steven Groves BASc of Research Project: The Desire to Acquire: Forecasting the Evolution of Household Energy Services Report No, and gasoline. A fixed effects panel model was used to examine the relationship of demand for energy

  14. Airplanes Aloft as a Sensor Network for Wind Forecasting

    E-Print Network [OSTI]

    Horvitz, Eric

    Airplanes Aloft as a Sensor Network for Wind Forecasting Ashish Kapoor, Zachary Horvitz, Spencer for observing weather phenomena at a continental scale. We focus specifically on the problem of wind forecasting with the sensed winds. The experiments show the promise of using airplane in flight as a large-scale sensor

  15. Classification of Commodity Price Forecast With Random Forests and Bayesian

    E-Print Network [OSTI]

    Freitas, Nando de

    on the sentiment of price39 forecasts and reports for commodities such as gold, natural gas or most commonly oil or natural gas can impact everything from the21 critical business decisions made within nationsClassification of Commodity Price Forecast Sentiment With Random Forests and Bayesian Optimization

  16. Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    114 Solar Irradiance And Power Output Variabilityand L. Bangyin. Online 24-h solar power forecasting based onNielsen. Online short-term solar power forecasting. Solar

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of numerical weather prediction solar irradiance forecasts numerical weather prediction model for solar irradiance weather prediction for intra?day solar  forecasting in the 

  18. Building Electricity Load Forecasting via Stacking Ensemble Learning Method with Moving Horizon Optimization

    E-Print Network [OSTI]

    Burger, Eric M.; Moura, Scott J.

    2015-01-01

    K. W. Yau, “Predicting electricity energy con- sumption: Afor building-level electricity load forecasts,” Energy andannealing algorithms in electricity load forecasting,”

  19. Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts ............................................................................................................................ 5 U.S. Natural Gas Commodity Prices

  20. Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA

    SciTech Connect (OSTI)

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

    2014-10-27

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

  1. Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

    Comparison of AEO 2009 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

  2. Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01

    Comparison of AEO 2008 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01

    Comparison of AEO 2006 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

  4. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

    Comparison of AEO 2007 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

  5. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    to  predict daily solar radiation.   Agriculture and Forest and Chuo, S.   2008.  Solar radiation forecasting using Short?term forecasting of solar radiation:   A statistical 

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

    Reports and Publications (EIA)

    2010-01-01

    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.

  7. Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy

    SciTech Connect (OSTI)

    Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

    2011-10-01

    The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

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

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    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.

  9. Towards a Dynamic Data Driven Application System for Wildfire Simulation

    E-Print Network [OSTI]

    Knyazev, Andrew

    -time weather data, images, and sensor streams. The system should change the forecast when new data is received (DDDAS) for short-range forecast of wildfire behavior with models steered by real-time weather data, images, and sensor streams. The forecast should be based on all available data, such as fuel maps

  10. Colibri: Towards a New Generation of Advanced Planning Systems

    E-Print Network [OSTI]

    Boyer, Edmond

    forecasting consists in forecasting future sales based on past sales. In a company, one or several forecasters a company to another. However, in gen- eral, this period concerns the twelve future months. 4. Future salesColibri: Towards a New Generation of Advanced Planning Systems Fatoumata Camara Objet Direct

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

    SciTech Connect (OSTI)

    Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M.

    2009-10-09

    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.

  12. Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

    SciTech Connect (OSTI)

    Jacobs, John M.; Rhodes, M.; Brown, C. W.; Hood, Raleigh R.; Leight, A.; Long, Wen; Wood, R.

    2014-11-01

    The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

  13. CloudCast: Cloud Computing for Short-term Mobile Weather Forecasts

    E-Print Network [OSTI]

    Shenoy, Prashant

    of Massachusetts Amherst Abstract--Since today's weather forecasts only cover large regions every few hours algorithm for generating accurate short-term weather forecasts. We study CloudCast's design space, which One useful application is mobile weather forecasting, which provides hour-to-hour forecasts

  14. Smard Grid Software Applications for Distribution Network Load Forecasting Eugene A. Feinberg, Jun Fei

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    of the distribution network. Keywords: load forecasting, feeder, transformer, load pocket, SmartGrid I. INTRODUCTION

  15. Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    Solar irradiance data . . . . . . . . . . . . .Irradiance . . . . . . . . . . . . . . . . . . . . . . . . . . .4 Forecasting Solar Irradiance With GOES-West Satellite

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

    E-Print Network [OSTI]

    Raftery, Adrian

    Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction LE proposes an effective bias correction technique for wind direction forecasts from numerical weather forecasts. These techniques are applied to 48-h forecasts of surface wind direction over the Pacific

  17. Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

    Office of Energy Efficiency and Renewable Energy (EERE)

    Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

  18. Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    Solar irradiance data . . . . . . . . . . . . .Accuracy . . . . . . . . . . . . . . . . . Solar Resourcev Uncertainty In Solar Resource: Forecasting

  19. USING BOX-JENKINS MODELS TO FORECAST FISHERY DYNAMICS: IDENTIFICATION, ESTIMATION, AND CHECKING

    E-Print Network [OSTI]

    ~ is illustrated by developing a model that makes monthly forecasts of skipjack tuna, Katsuwonus pelamis, catches

  20. Improved forecasts of extreme weather events by future space borne Doppler wind lidar

    E-Print Network [OSTI]

    Marseille, Gert-Jan

    of forecast failures, in particular those with large socio economic impact. Forecast failures of high- impact on their ability to improve meteorological analyses and subsequently reduce the probability of forecast failures true atmospheric state. This was generated by the European Centre for Medium-Range Weather Forecasts

  1. The new Athens Center applied to Space Weather Forecasting

    SciTech Connect (OSTI)

    Mavromichalaki, H.; Sarlanis, C.; Souvatzoglou, G.; Mariatos, G.; Gerontidou, M.; Plainaki, C.; Papaioannou, A.; Tatsis, S. [University of Athens, Physics Department, Section of Nuclear and Particle Physics, Zografos 15771 Athens (Greece); Belov, A.; Eroshenko, E.; Yanke, V. [IZMIRAN, Russian Academy of Science, 1420092 Moscow (Russian Federation)

    2006-08-25

    The Sun provides most of the initial energy driving space weather and modulates the energy input from sources outside the solar system, but this energy undergoes many transformations within the various components of the solar-terrestrial system, which is comprised of the solar wind, magnetosphere and radiation belts, the ionosphere, and the upper and lower atmospheres of Earth. This is the reason why an Earth's based neutron monitor network can be used in order to produce a real time forecasting of space weather phenomena.Since 2004 a fully functioned new data analysis Center in real-time is in operation in Neutron Monitor Station of Athens University (ANMODAP Center) suitable for research applications. It provides a multi sided use of twenty three neutron monitor stations distributing in all world and operating in real-time given crucial information on space weather phenomena. In particular, the ANMODAP Center can give a preliminary alert of ground level enhancements (GLEs) of solar cosmic rays which can be registered around 20 to 30 minutes before the main part of lower energy particles. Therefore these energetic solar cosmic rays provide the advantage of forth warning. Moreover, the monitoring of the precursors of cosmic rays gives a forehand estimate on that kind of events should be expected (geomagnetic storms and/or Forbush decreases)

  2. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Solar Trackers Market Forecast Home John55364's picture Submitted by John55364(100) Contributor 12 May, 2015 - 03:54 Solar Trackers Market - Global Industry Analysis, Size, Share,...

  3. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    G. Bel; C. P. Connaughton; M. Toots; M. M. Bandi

    2015-03-29

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  4. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

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

  5. Forecasting and Risk Analysis in Supply Chain Management

    E-Print Network [OSTI]

    Hilmola, Olli-Pekka

    Forecasting is an underestimated field of research in supply chain management. Recently advanced methods are coming into use. Initial results are encouraging, but often require changes in policies for collaboration and ...

  6. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

    Through the Improving the Accuracy of Solar Forecasting Funding Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and other...

  7. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

    low electricity and natural gas rates, and relatively low efficiency program and self Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert Oglesby Executive Director DISCLAIMER Staff for electric vehicles. #12;ii #12;iii ABSTRACT The Preliminary California Energy Demand Forecast 2012

  8. Optimally Controlling Hybrid Electric Vehicles using Path Forecasting

    E-Print Network [OSTI]

    Kolmanovsky, Ilya V.

    The paper examines path-dependent control of Hybrid Electric Vehicles (HEVs). In this approach we seek to improve HEV fuel economy by optimizing charging and discharging of the vehicle battery depending on the forecasted ...

  9. Multidimensional approaches to performance evaluation of competing forecasting models 

    E-Print Network [OSTI]

    Xu, Bing

    2009-01-01

    The purpose of my research is to contribute to the field of forecasting from a methodological perspective as well as to the field of crude oil as an application area to test the performance of my methodological contributions ...

  10. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    Bel, G; Toots, M; Bandi, M M

    2015-01-01

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  11. Optimally controlling hybrid electric vehicles using path forecasting

    E-Print Network [OSTI]

    Katsargyri, Georgia-Evangelina

    2008-01-01

    Hybrid Electric Vehicles (HEVs) with path-forecasting belong to the class of fuel efficient vehicles, which use external sensory information and powertrains with multiple operating modes in order to increase fuel economy. ...

  12. Mesoscale predictability and background error convariance estimation through ensemble forecasting 

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01

    Over the past decade, ensemble forecasting has emerged as a powerful tool for numerical weather prediction. Not only does it produce the best estimate of the state of the atmosphere, it also could quantify the uncertainties ...

  13. Forecasting and strategic inventory placement for gas turbine aftermarket spares

    E-Print Network [OSTI]

    Simmons, Joshua T. (Joshua Thomas)

    2007-01-01

    This thesis addresses the problem of forecasting demand for Life Limited Parts (LLPs) in the gas turbine engine aftermarket industry. It is based on work performed at Pratt & Whitney, a major producer of turbine engines. ...

  14. Dispersion in analysts' forecasts: does it make a difference? 

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30

    Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack...

  15. Radiation fog forecasting using a 1-dimensional model 

    E-Print Network [OSTI]

    Peyraud, Lionel

    2001-01-01

    weather patterns known to be favorable for producing fog and once it has formed, to state that it will persist unless the pattern changes. Unfortunately, while such methods have shown some success, many times they have led weather forecasters astray...

  16. Pressure Normalization of Production Rates Improves Forecasting Results 

    E-Print Network [OSTI]

    Lacayo Ortiz, Juan Manuel

    2013-08-07

    reliable production forecasting technique suited to interpret unconventional wells in specific situations such as unstable operating conditions, limited availability of production data (short production history) and high-pressure, rate-restricted wells...

  17. Forecasting Stock Market Volatility: Evidence from Fourteen Countries. 

    E-Print Network [OSTI]

    Balaban, Ercan; Bayar, Asli; Faff, Robert

    2002-01-01

    This paper evaluates the out-of-sample forecasting accuracy of eleven models for weekly and monthly volatility in fourteen stock markets. Volatility is defined as within-week (within-month) standard deviation of continuously ...

  18. Adaptive sampling and forecasting with mobile sensor networks

    E-Print Network [OSTI]

    Choi, Han-Lim

    2009-01-01

    This thesis addresses planning of mobile sensor networks to extract the best information possible out of the environment to improve the (ensemble) forecast at some verification region in the future. To define the information ...

  19. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Menut, Laurent

    , French legislation has been adapted in such a way that the local authorities in charge of air pollution can now inform the public and take emergency decisions re- lated to air pollution control not onlyOLOGICAL SOCIETy | #12;air quality monitoring system. In case of a pollution episode, when concentrations exceed

  1. Forecasting the probability of forest fires in Northeast Texas 

    E-Print Network [OSTI]

    Wadleigh, Stuart Allen

    1972-01-01

    FORECASTING THE PROBABILITY OF FOREST FIRES IN NORTHEAST TEXAS A Thesis by STUART ALLEN WADLEIGH Submit ted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE... December 1972 Major Subject: Meteorology FORECASTING THE PROBABILITY OF FOREST FIRES IN NORTHEAST TEXAS A Thesis by STUART ALLEN WADLEIGH Approved as to style and content by: ( irman of ee) (Head of Depar nt) (Member) (Member) December 1972 c...

  2. Forecasting potential project risks through leading indicators to project outcome 

    E-Print Network [OSTI]

    Choi, Ji Won

    2007-09-17

    for the degree of MASTER OF SCIENCE May 2007 Major Subject: Civil Engineering FORECASTING POTENTIAL PROJECT RISKS THROUGH LEADING INDICATORS TO PROJECT OUTCOME A Thesis by JI WON CHOI... Guikema Head of Department, David Rosowsky May 2007 Major Subject: Civil Engineering iii ABSTRACT Forecasting Potential Project Risks through Leading Indicators to Project Outcome. (May 2007) Ji Won Choi, B.S., Han-Yang University...

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

    E-Print Network [OSTI]

    Douches, David S.

    Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database Kathleen Baker a, , Paul Roehsner a , Thomas Lake b , Douglas Rivet

  4. Weather-based forecasts of California crop yields

    SciTech Connect (OSTI)

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

    2005-09-26

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

  5. Value of Probabilistic Weather Forecasts: Assessment by Real-Time Optimization of Irrigation Scheduling

    SciTech Connect (OSTI)

    Cai, Ximing; Hejazi, Mohamad I.; Wang, Dingbao

    2011-09-29

    This paper presents a modeling framework for real-time decision support for irrigation scheduling using the National Oceanic and Atmospheric Administration's (NOAA's) probabilistic rainfall forecasts. The forecasts and their probability distributions are incorporated into a simulation-optimization modeling framework. In this study, modeling irrigation is determined by a stochastic optimization program based on the simulated soil moisture and crop water-stress status and the forecasted rainfall for the next 1-7 days. The modeling framework is applied to irrigated corn in Mason County, Illinois. It is found that there is ample potential to improve current farmers practices by simply using the proposed simulation-optimization framework, which uses the present soil moisture and crop evapotranspiration information even without any forecasts. It is found that the values of the forecasts vary across dry, normal, and wet years. More significant economic gains are found in normal and wet years than in dry years under the various forecast horizons. To mitigate drought effect on crop yield through irrigation, medium- or long-term climate predictions likely play a more important role than short-term forecasts. NOAA's imperfect 1-week forecast is still valuable in terms of both profit gain and water saving. Compared with the no-rain forecast case, the short-term imperfect forecasts could lead to additional 2.4-8.5% gain in profit and 11.0-26.9% water saving. However, the performance of the imperfect forecast is only slightly better than the ensemble weather forecast based on historical data and slightly inferior to the perfect forecast. It seems that the 1-week forecast horizon is too limited to evaluate the role of the various forecast scenarios for irrigation scheduling, which is actually a seasonal decision issue. For irrigation scheduling, both the forecast quality and the length of forecast time horizon matter. Thus, longer forecasts might be necessary to evaluate the role of forecasts for irrigation scheduling in a more effective way.

  6. Nonlinear Dynamics, Magnitude-Period Formula and Forecasts on Earthquake

    E-Print Network [OSTI]

    Yi-Fang Chang

    2008-02-02

    Based on the geodynamics, an earthquake does not take place until the momentum-energy excess a faulting threshold value of rock due to the movement of the fluid layer under the rock layer and the transport and accumulation of the momentum. From the nonlinear equations of fluid mechanics, a simplified nonlinear solution of momentum corresponding the accumulation of the energy could be derived. Otherwise, a chaos equation could be obtained, in which chaos corresponds to the earthquake, which shows complexity on seismology, and impossibility of exact prediction of earthquakes. But, combining the Carlson-Langer model and the Gutenberg-Richter relation, the magnitude-period formula of the earthquake may be derived approximately, and some results can be calculated quantitatively. For example, we forecast a series of earthquakes of 2004, 2009 and 2014, especially in 2019 in California. Combining the Lorenz model, we discuss the earthquake migration to and fro. Moreover, many external causes for earthquake are merely the initial conditions of this nonlinear system.

  7. Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems

    E-Print Network [OSTI]

    Nottrott, A.; Kleissl, J.; Washom, B.

    2013-01-01

    PV systems using storage and controls, Solar Energy 81(7) (of solar and load forecasting in demand side energy storageEnergy storage, Forecasting, Optimal scheduling, Solar power

  8. Results from the Second Forum on the Future Role of the Human in the Forecast Process. Part II: Cognitive Psychological Aspects of Expert Weather Forecasters

    E-Print Network [OSTI]

    Schultz, David

    : Cognitive Psychological Aspects of Expert Weather Forecasters NEIL A. STUART* NOAA/National Weather Service of Applied Research Associates, Fairborn, Ohio In Preparation for Submission to Forecasters Forum, Weather and Forecasting 30 June 2006 Corresponding author address: Neil A. Stuart, National Weather Service, 10009 General

  9. Wind power forecasting : state-of-the-art 2009.

    SciTech Connect (OSTI)

    Monteiro, C.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

    2009-11-20

    Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem.

  10. Forecasting the 2013–2014 influenza season using Wikipedia

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are appliedmore »to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.« less

  11. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

    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.

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

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23

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

  14. Use of Data Denial Experiments to Evaluate ESA Forecast Sensitivity Patterns

    SciTech Connect (OSTI)

    Zack, J; Natenberg, E J; Knowe, G V; Manobianco, J; Waight, K; Hanley, D; Kamath, C

    2011-09-13

    The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height ({approx}80 m). In this phase of the project the focus is on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The Ensemble Sensitivity Analysis (ESA) approach uses data generated by a set (ensemble) of perturbed numerical weather prediction (NWP) simulations for a sample time period to statistically diagnose the sensitivity of a specified forecast variable (metric) for a target location to parameters at other locations and prior times referred to as the initial condition (IC) or state variables. The ESA approach was tested on the large-scale atmospheric prediction problem by Ancell and Hakim 2007 and Torn and Hakim 2008. ESA was adapted and applied at the mesoscale by Zack et al. (2010a, b, and c) to the Tehachapi Pass, CA (warm and cools seasons) and Mid-Colombia Basin (warm season only) wind generation regions. In order to apply the ESA approach at the resolution needed at the mesoscale, Zack et al. (2010a, b, and c) developed the Multiple Observation Optimization Algorithm (MOOA). MOOA uses a multivariate regression on a few select IC parameters at one location to determine the incremental improvement of measuring multiple variables (representative of the IC parameters) at various locations. MOOA also determines how much information from each IC parameter contributes to the change in the metric variable at the target location. The Zack et al. studies (2010a, b, and c), demonstrated that forecast sensitivity can be characterized by well-defined, localized patterns for a number of IC variables such as 80-m wind speed and vertical temperature difference. Ideally, the data assimilation scheme used in the experiments would have been based upon an ensemble Kalman filter (EnKF) that was similar to the ESA method used to diagnose the Mid-Colombia Basin sensitivity patterns in the previous studies. However, the use of an EnKF system at high resolution is impractical because of the very high computational cost. Thus, it was decided to use the three-dimensional variational analysis data assimilation that is less computationally intensive and more economically practical for generating operational forecasts. There are two tasks in the current project effort designed to validate the ESA observational system deployment approach in order to move closer to the overall goal: (1) Perform an Observing System Experiment (OSE) using a data denial approach which is the focus of this task and report; and (2) Conduct a set of Observing System Simulation Experiments (OSSE) for the Mid-Colombia basin region. The results of this task are presented in a separate report. The objective of the OSE task involves validating the ESA-MOOA results from the previous sensitivity studies for the Mid-Columbia Basin by testing the impact of existing meteorological tower measurements on the 0- to 6-hour ahead 80-m wind forecasts at the target locations. The testing of the ESA-MOOA method used a combination of data assimilation techniques and data denial experiments to accomplish the task objective.

  15. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    2008-01-15

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

  16. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

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

  17. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; et al

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we havemore »the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.« less

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

    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.

  19. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

    Comparison of AEO 2007 Natural Gas Price Forecast to NYMEXs reference case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

  20. Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

    Comparison of AEO 2009 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01

    Comparison of AEO 2006 Natural Gas Price Forecast to NYMEXs reference case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

  2. Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01

    late January 2008, extend its natural gas futures strip anComparison of AEO 2008 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

    the AEO 2005 reference case oil price forecast and NYMEX oibasis-adjusted NYMEX crude oil futures con tracts fo r 2010more than the reference case oil price forecast for that

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

    E-Print Network [OSTI]

    Bush, Sarah, 1973-

    2003-01-01

    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+ ...

  5. ESTIMATING POTENTIAL SEVERE WEATHER SOCIETAL IMPACTS USING PROBABILISTIC FORECASTS ISSUED BY THE NWS STORM PREDICTION CENTER

    E-Print Network [OSTI]

    effort to estimate potential severe weather societal impacts based on a combination of probabilistic forecasts and high resolution population data. For equal severe weather threat, events that occur over1 ESTIMATING POTENTIAL SEVERE WEATHER SOCIETAL IMPACTS USING PROBABILISTIC FORECASTS ISSUED

  6. Generating day-of-operation probabilistic capacity scenarios from weather forecasts

    E-Print Network [OSTI]

    Buxi, Gurkaran

    2012-01-01

    0400Z on the 18 th the wind is forecast at 15Knots blowingforecast for the day for the quarter-hour period , representing the windthe forecast is valid. The TAF predicts the wind speed, wind

  7. Earnings Management Pressure on Audit Clients: Auditor Response to Analyst Forecast Signals 

    E-Print Network [OSTI]

    Newton, Nathan J.

    2013-06-26

    This study investigates whether auditors respond to earnings management pressure created by analyst forecasts. Analyst forecasts create an important earnings target for management, and professional standards direct auditors to consider how...

  8. Error growth in poor ECMWF forecasts over the contiguous United States 

    E-Print Network [OSTI]

    Modlin, Norman Ray

    1993-01-01

    Successive improvements to the European Center for Medium-range Weather Forecasting model have resulted in improved forecast performance over the Contiguous United States (CONUS). While the overall performance of the model ...

  9. Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General Circulation Models

    E-Print Network [OSTI]

    Arumugam, Sankar

    Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater

  10. A supply forecasting model for Zimbabwe's corn sector: a time series and structural analysis 

    E-Print Network [OSTI]

    Makaudze, Ephias

    1993-01-01

    Board's financial resource needs. Thus, the corn supply forecasts are important information used by the government for contingency planning, decision-making, policy-formulation and implementation. As such, the need for accurate forecasts is obvious...

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

    E-Print Network [OSTI]

    Statton, James Cody

    2012-07-16

    . This study suggests a type curve is most useful when 24 months or less is available to forecast. The SEPD model generally provides more conservative forecasts and EUR estimates than Arps' model with a minimum decline rate of 5%....

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

    E-Print Network [OSTI]

    Ganguly, Auroop Ratan

    2002-01-01

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

  13. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

    Figure 9: Two Alternative Price Forecasts (denoted by openComparison of AEO 2007 Natural Gas Price Forecast toNYMEX Futures Prices Date: December 6, 2006 Introduction On

  14. Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    and forecasting of solar radiation data: a review. Int. J.beam and global solar radiation data. Solar Energy , 81:768–forecasting of solar radiation data: a review. International

  15. Plan for the Joint Ensemble Forecast System (JEFS)

    E-Print Network [OSTI]

    Mass, Clifford F.

    by the High Performance Computing Modernization Program. Phase I will produce one of the DDC project

  16. Forecast-driven tactical planning models for manufacturing systems

    E-Print Network [OSTI]

    Chhaochhria, Pallav

    2011-01-01

    Our work is motivated by real-world planning challenges faced by a manufacturer of industrial products. In the first part of the thesis, we study a multi-product serial-flow production line that operates in a low-volume, ...

  17. OpenEI Community - Microturbine Systems Market Forecast

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo, Maryland:NPI VenturesNewSt.Information OlindaOnslow County,OpTICOpenBarter Jump

  18. Microturbine Systems Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsource HistoryScenariosMarysvilleMicrogravity-Hybrid Microgravity

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

    SciTech Connect (OSTI)

    Xu, Lilai; Gao, Peiqing; Cui, Shenghui; Liu, Chun

    2013-06-15

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

  20. Central Wind Power Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

    The report addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America.

  1. Journal of Atmospheric and Solar-Terrestrial Physics 66 (2004) 14911497 Sun-to-magnetosphere modeling: CISM forecast model

    E-Print Network [OSTI]

    2004-01-01

    -to-magnetosphere modeling: CISM forecast model development using linked empirical methods D.N. Bakera,Ã, R.S. Weigela , E Space Weather Modeling (CISM) is to provide linked end-to- end models of the connected Sun­Earth system. It is envisioned that the ultimate product of the CISM effort will be a single, physics-based (i.e., ``forward

  2. Managing Wind Power Forecast Uncertainty in Electric Grids Submitted in partial fulfillment of the requirements for

    E-Print Network [OSTI]

    Instituto de Sistemas e Robotica

    Managing Wind Power Forecast Uncertainty in Electric Grids Submitted in partial fulfillment;iii Abstract Electricity generated from wind power is both variable and uncertain. Wind forecasts prices. Wind power forecast errors for aggregated wind farms are often modeled with Gaussian

  3. Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines

    E-Print Network [OSTI]

    Cañizares, Claudio A.

    for forecasting the Spanish electricity market prices. On the other hand, ARIMA, dynamic regression and transfer been used to forecast the Spanish market prices [7], [9], Californian market prices [9], Leipzig power have been used for forecasting the Spanish and Californian market prices [11] and the PJM market prices

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

    E-Print Network [OSTI]

    Irwin, Mark E.

    2005-01-01

    conditional on observed (or forecasted) meteorology including temperature, humidity, pressure, and wind speed, defining the spatial­temporal extent of episodes of dangerous air quality, forecasting urban and areaAtmospheric Environment 39 (2005) 1373­1382 A hierarchical Bayesian model to estimate and forecast

  5. A Comparison of Bayesian and Conditional Density Models in Probabilistic Ozone Forecasting

    E-Print Network [OSTI]

    Hsieh, William

    A Comparison of Bayesian and Conditional Density Models in Probabilistic Ozone Forecasting Song Cai to provide predictive distributions of daily maximum surface level ozone concentrations. Five forecast models forecasts for extreme events, namely poor air quality events defined as having ozone concentration 82 ppb

  6. Bias reduction in the Sea Surface Temperature (SST) forecasts based on GOES satellite data

    E-Print Network [OSTI]

    Kurapov, Alexander

    Bias reduction in the Sea Surface Temperature (SST) forecasts based on GOES satellite data Based on comparisons with infrared (GOES) and microwave (AMSE-R) satellite data, our coastal ocean forecast model set circulation model and satellite data helps to improve forecasting of ocean conditions (esp. currents and SST

  7. Short Term Electricity Price Forecasting in the Nordic Region Anders Lund Eriksrud

    E-Print Network [OSTI]

    Lavaei, Javad

    Short Term Electricity Price Forecasting in the Nordic Region Anders Lund Eriksrud May 11, 2014 Abstract This paper presents a survey of electricity price forecasting for the Nordic region, and performs that time series models more appropriate for forecasting electricity prices, compared to machine learning

  8. Influence of Spikes in the Short-term Electricity Price Forecasting

    E-Print Network [OSTI]

    Friedl, Herwig

    Influence of Spikes in the Short-term Electricity Price Forecasting Vika Koban, Milos Pantos of electricity price under normal conditions with the spike time series caused by extreme conditions in order to obtain a better forecast of the spot price. Short term electricity price forecasting has become

  9. Detrending Daily Natural Gas Consumption Series to Improve Short-Term Forecasts

    E-Print Network [OSTI]

    Povinelli, Richard J.

    Detrending Daily Natural Gas Consumption Series to Improve Short-Term Forecasts Ronald H. Brown1 that allows long-term natural gas demand signals to be used effect- ively to generate high quality short-term natural gas demand forecasting models. Short data sets in natural gas forecasting inadequately represent

  10. Application of a new phenomenological coronal mass ejection model to space weather forecasting

    E-Print Network [OSTI]

    Howard, Tim

    to space weather forecasting T. A. Howard1 and S. J. Tappin2 Received 15 October 2009; revised 27 April with the Earth. Hence the model can be used for space weather forecasting. We present a preliminary evaluation to fully validate it for integration with existing tools for space weather forecasting. Citation: Howard, T

  11. Reprinted from: Proceedings, International Workshop on Observations/Forecasting of Meso-scale Severe Weather and

    E-Print Network [OSTI]

    Doswell III, Charles A.

    -scale Severe Weather and Technology of Reduction of Relevant Disasters (Tokyo, Japan), 22-26 February 1993, 181 on the ingredients for particular severe weather events, a focus is provided for the forecasting process of forecasters is discussed also, as a necessary component in a balanced approach to weather forecasting

  12. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    basis of data from the Energy Supply Planning Model [9] andeconomic resources will energy supply system. r role in diconstructed an integrated energy supply~demand November 18,

  13. Production Forecast, Analysis and Simulation of Eagle Ford Shale Oil 

    E-Print Network [OSTI]

    Alotaibi, Basel Z S Z J

    2014-12-02

    is to generate field-wide production forecast of the Eagle Ford Shale (EFS). This study considered oil production of the EFS only. More than 6 thousand oil wells were put online in the EFS basin between 2008 and December 2013. The method started by generating...

  14. Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts

    E-Print Network [OSTI]

    Garulli, Andrea

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

  15. Forecasting stock prices using Genetic Programming and Chance Discovery

    E-Print Network [OSTI]

    Fernandez, Thomas

    finance. GAs are algorithms that emulate evolution and natural selection to solve a problem. A populationForecasting stock prices using Genetic Programming and Chance Discovery Alma Lilia Garcia to financial problems. In particular, the use of Genetic Algorithms (GAs), for financial purposes, has

  16. Power Forecasting for Plug-in Electric Vehicles

    E-Print Network [OSTI]

    Lavaei, Javad

    Power Forecasting for Plug-in Electric Vehicles with Statistic Simulations Guangbin Li (gl2423) #12 of the most heated-discussed issues. Energy shortage and environment pollution are the main bottleneck the tradeoff between energy supply and environment pollution. As the international oil price was continuously

  17. Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will tak

    E-Print Network [OSTI]

    Islam, M. Saif

    is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey on your needs for information on solar energy resources and forecasting. This survey is conducted with the California Solar Energy Collaborative (CSEC) and the California Solar Initiative (CSI) our objective

  18. A Hierarchical Pattern Learning Framework for Forecasting Extreme Weather Events

    E-Print Network [OSTI]

    Ding, Wei

    . Frequent pattern-based data representations have been used in various studies for abstracting climaticA Hierarchical Pattern Learning Framework for Forecasting Extreme Weather Events Dawei Wang, Wei@cs.umb.edu Abstract--Extreme weather events, like extreme rainfalls, are severe weather hazards and also the triggers

  19. ARM Processes and Their Modeling and Forecasting Methodology Benjamin Melamed

    E-Print Network [OSTI]

    Chapter 73 ARM Processes and Their Modeling and Forecasting Methodology Benjamin Melamed Abstract The class of ARM (Autoregressive Modular) processes is a class of stochastic processes, defined by a non- linear autoregressive scheme with modulo-1 reduction and additional transformations. ARM processes

  20. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    /Individuals Providing Comments California Natural Gas Vehicle Coalition/ Mike Eaves League of Women VotersCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY AND TRANSPORTATION DIVISION B. B. Blevins Executive Director DISCLAIMER This report was prepared by a California

  1. Detecting and Forecasting Economic Regimes in Automated Exchanges

    E-Print Network [OSTI]

    Ketter, Wolfgang

    Detecting and Forecasting Economic Regimes in Automated Exchanges Wolfgang Ketter , John Collins. of Mgmt., Erasmus University Dept. of Computer Science and Engineering, University of Minnesota Dept,gini,schrater}@cs.umn.edu, agupta@csom.umn.edu Abstract We present basic building blocks of an agent that can use observable market

  2. Detecting and Forecasting Economic Regimes in Automated Exchanges

    E-Print Network [OSTI]

    Ketter, Wolfgang

    Detecting and Forecasting Economic Regimes in Automated Exchanges Wolfgang Ketter # , John Collins, Rotterdam Sch. of Mgmt., Erasmus University + Dept. of Computer Science and Engineering, University wketter@rsm.nl, {jcollins,gini,schrater}@cs.umn.edu, agupta@csom.umn.edu Abstract We present basic

  3. URBAN OZONE CONCENTRATION FORECASTING WITH ARTIFICIAL NEURAL NETWORK IN CORSICA

    E-Print Network [OSTI]

    Boyer, Edmond

    Perceptron; Ozone concentration. 1. Introduction Tropospheric ozone is a major air pollution problem, both, Ajaccio, France, e-mail: balu@univ-corse.fr Abstract: Atmospheric pollutants concentration forecasting is an important issue in air quality monitoring. Qualitair Corse, the organization responsible for monitoring air

  4. Review of Wind Energy Forecasting Methods for Modeling Ramping Events

    SciTech Connect (OSTI)

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

    2011-03-28

    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.

  5. 1. Introduction Users of weather forecasts, particularly paying cus-

    E-Print Network [OSTI]

    1. Introduction Users of weather forecasts, particularly paying cus- tomers, are operating within Kingdom out of a total budget of approximately £140 million for winter road maintenance. It is difficult rely on a simple set of statistics provided by the weather service providers. The current guidance

  6. Forecasting Hourly Electricity Load Profile Using Neural Networks

    E-Print Network [OSTI]

    Koprinska, Irena

    Forecasting Hourly Electricity Load Profile Using Neural Networks Mashud Rana and Irena Koprinska--We present INN, a new approach for predicting the hourly electricity load profile for the next day from a time series of previous electricity loads. It uses an iterative methodology to make the predictions

  7. Journey data based arrival forecasting for bicycle hire schemes

    E-Print Network [OSTI]

    Imperial College, London

    Journey data based arrival forecasting for bicycle hire schemes Marcel C. Guenther and Jeremy T. The global emergence of city bicycle hire schemes has re- cently received a lot of attention of future bicycle migration trends, as these assist service providers to ensure availability of bicycles

  8. Numerical Weather Forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L.

    1999-01-26

    Facilities such as the Savannah River Site (SRS), which contain the potential for hazardous atmospheric releases, rely on the predictive capabilities of dispersion models to assess possible emergency response actions. The operational design in relation to domain size and forecast time is presented, along with verification of model results over extended time periods with archived surface observations.

  9. Forecasting Hospital Bed Availability Using Simulation and Neural Networks

    E-Print Network [OSTI]

    Kuhl, Michael E.

    Forecasting Hospital Bed Availability Using Simulation and Neural Networks Matthew J. Daniels, NY 14623 Elisabeth Hager Hager Consulting Pittsford, NY 14534 Abstract The availability of beds is a critical factor for decision-making in hospitals. Bed availability (or alternatively the bed occupancy

  10. FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH

    E-Print Network [OSTI]

    Perez, Richard R.

    a limited evaluation of its performance against ground-measured and satellite-derived irradiances in AlbanyFORECASTING SOLAR RADIATION -- PRELIMINARY EVALUATION OF AN APPROACH BASED UPON THE NATIONAL NREL, 1617 Cole Blvd. Golden, CO 80841 stephen_wilcox@nrel.gov Antoine Zelenka Meteosuisse

  11. Assessing forecast uncertainties in a VECX model for Switzerland: an exercise in forecast combination across models and observation windows

    E-Print Network [OSTI]

    Assenmacher-Wesche, Katrin; Pesaran, M. Hashem

    horizons of up to eight quarters ahead since this is the rele- vant time horizon for central banks when setting interest rates. Table 6 shows the RMSFE, the bias and the hit rate of forecasts based on the VECX*(2,2) model for the longest estimation window...

  12. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    Oahu Development of geothermal energy can be pro~ moted only13 Role of Renewables Geothermal energy cabL;; system tv:illQ New Techno of hence geothermal energy would be available

  13. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    type of power plant and on the generating capacity of eachplant would therma.l storage system, This would permit extended use of solar thennal We energy for generating

  14. A Rank Approach to Equity Forecast Construction

    E-Print Network [OSTI]

    Satchell, Stephen E.; Wright, Stephen M.

    2006-03-14

    , evolution and exogenous events. Such “one-offs” as leaving the European Monetary System, September 11th, October 1987, the Tequila crisis etcetera etcetera, may be capable of being modelled within a conventional statistical structure but it is probably...

  15. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatist...

    E-Print Network [OSTI]

    Raftery, Adrian

    permission. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatist... Yulia Gel; Adrian

  16. Algorithms for bispectra: forecasting, optimal analysis, and simulation

    E-Print Network [OSTI]

    Kendrick M. Smith; Matias Zaldarriaga

    2011-11-08

    We propose a factorizability ansatz for angular bispectra which permits fast algorithms for forecasting, analysis, and simulation, yet is general enough to encompass many interesting CMB bispectra. We describe a suite of general algorithms which apply to any bispectrum which can be represented in factorizable form. First, we present algorithms for Fisher matrix forecasts and the related problem of optimizing the factorizable representation, giving a Fisher forecast for Planck as an example. We show that the CMB can give independent constraints on the amplitude of primordial bispectra of both local and equilateral shape as well as those created by secondary anisotropies. We also show that the ISW-lensing bispectrum should be detected by Planck and could bias estimates of the local type of non-Gaussianity if not properly accounted for. Second, we implement a bispectrum estimator which is fully optimal in the presence of sky cuts and inhomogeneous noise, extends the generality of fast estimators which have been limited to a few specific forms of the bispectrum, and improves the running time of existing implementations by several orders of magnitude. Third, we give an algorithm for simulating random, weakly non-Gaussian maps with prescribed power spectrum and factorizable bispectrum.

  17. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.

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

    SciTech Connect (OSTI)

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

    2012-08-15

    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.

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

    E-Print Network [OSTI]

    Baran, Sándor

    2014-01-01

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

  20. Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

    The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

  1. Risk analysis for species introductions: forecasting population growth of Eurasian ruffe

    E-Print Network [OSTI]

    Risk analysis for species introductions: forecasting population growth of Eurasian ruffe productivity (Leung et al. 2002). Risk-analysis methodology for intentional and unintentional introductions

  2. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    Numerical Weather Prediction (NWP), Solar Forecasting  1.   to more accurate prediction of solar  irradiance, given a to create daily solar electricity predictions accurate to 

  3. Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

    Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

  4. Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand .............................................................. 23 Electricity Demand Growth in the West............................................................................................................................... 28 Estimating Electricity Demand in Data Centers

  5. Report of the External Expert Peer Review Panel: DOE Benefits Forecasts

    SciTech Connect (OSTI)

    2009-01-18

    A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts.

  6. Skill evaluation of water supply forecasts in western Sierra Nevada and Colorado River basins

    E-Print Network [OSTI]

    Harrison, Brent

    2014-01-01

    streamflow predictions for water supply forecasting in theAn assessment of seasonal water supply outlooks in thepaper, Dept. of Hydrology and Water Resources, University of

  7. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

    approach to evaluating price risk would be to use suchthe base-case natural gas price forecast, but to alsorange of different plausible price projections, using either

  8. Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

    range of different plausible price projections, using eitherthat renewables can provide price certainty over even longerof AEO 2009 Natural Gas Price Forecast to NYMEX Futures

  9. Neural network based short-term load forecasting using weather compensation

    SciTech Connect (OSTI)

    Chow, T.W.S.; Leung, C.T. [City Univ. of Hong Kong, Kowloon (Hong Kong). Dept. of Electronic Engineering] [City Univ. of Hong Kong, Kowloon (Hong Kong). Dept. of Electronic Engineering

    1996-11-01

    This paper presents a novel technique for electric load forecasting based on neural weather compensation. The proposed method is a nonlinear generalization of Box and Jenkins approach for nonstationary time-series prediction. A weather compensation neural network is implemented for one-day ahead electric load forecasting. The weather compensation neural network can accurately predict the change of actual electric load consumption from the previous day. The results, based on Hong Kong Island historical load demand, indicate that this methodology is capable of providing a more accurate load forecast with a 0.9% reduction in forecast error.

  10. Generating day-of-operation probabilistic capacity scenarios from weather forecasts

    E-Print Network [OSTI]

    Buxi, Gurkaran

    2012-01-01

    user needs for convective weather forecasts," in AmericanJ. Andrews M. Weber, "Weather Information Requirements forInt. Conf. on Aviation Weather, Paris, France. [5] NASDAC. (

  11. Modeling brine-rock interactions in an enhanced geothermal system deep fractured reservoir at Soultz-Sous-Forets (France): a joint approach using two geochemical codes: frachem and toughreact

    E-Print Network [OSTI]

    Andre, Laurent; Spycher, Nicolas; Xu, Tianfu; Vuataz, Francois-D.; Pruess, Karsten.

    2006-01-01

    geothermal systems (EGS). Proceedings 31 th Workshop onenhanced geothermal systems (EGS) to forecast the long-termdeveloped to investigate EGS, were applied to model the same

  12. Net Interchange Schedule Forecasting of Electric Power Exchange for RTO/ISOs

    SciTech Connect (OSTI)

    Ferryman, Thomas A.; Haglin, David J.; Vlachopoulou, Maria; Yin, Jian; Shen, Chao; Tuffner, Francis K.; Lin, Guang; Zhou, Ning; Tong, Jianzhong

    2012-07-26

    Neighboring independent system operators (ISOs) exchange electric power to enable efficient and reliable operation of the grid. Net interchange (NI) schedule is the sum of the transactions (in MW) between an ISO and its neighbors. Effective forecasting of the amount of actual NI can improve grid operation efficiency. This paper presents results of a preliminary investigation into various methods of prediction that may result in improved prediction accuracy. The methods studied are linear regression, forward regression, stepwise regression, and support vector machine (SVM) regression. The work to date is not yet conclusive. The hope is to explore the effectiveness of other prediction methods and apply all methods to at least one new data set. This should enable more confidence in the conclusions.

  13. Forecast of Contracting and Subcontracting Opportunities, Fiscal year 1995

    SciTech Connect (OSTI)

    Not Available

    1995-02-01

    Welcome to the US Department of Energy`s Forecast of Contracting and Subcontracting Opportunities. This forecast, which is published pursuant to Public Low 100--656, ``Business Opportunity Development Reform Act of 1988,`` is intended to inform small business concerns, including those owned and controlled by socially and economically disadvantaged individuals, and women-owned small business concerns, of the anticipated fiscal year 1995 contracting and subcontracting opportunities with the Department of Energy and its management and operating contractors and environmental restoration and waste management contractors. This document will provide the small business contractor with advance notice of the Department`s procurement plans as they pertain to small, small disadvantaged and women-owned small business concerns.Opportunities contained in the forecast support the mission of the Department, to serve as advocate for the notion`s energy production, regulation, demonstration, conservation, reserve maintenance, nuclear weapons and defense research, development and testing, when it is a national priority. The Department`s responsibilities include long-term, high-risk research and development of energy technology, the marketing of Federal power, and maintenance of a central energy data collection and analysis program. A key mission for the Department is to identify and reduce risks, as well as manage waste at more than 100 sites in 34 states and territories, where nuclear energy or weapons research and production resulted in radioactive, hazardous, and mixed waste contamination. Each fiscal year, the Department establishes contracting goals to increase contracts to small business concerns and meet our mission objectives.

  14. Inclusion of In-Situ Velocity Measurements into the UCSD Time-Dependent Tomography to Constrain and Better-Forecast Remote-Sensing Observations

    E-Print Network [OSTI]

    Jackson, B. V.; Hick, P. P.; Bisi, M. M.; Clover, J. M.; Buffington, A.

    2010-01-01

    time”. The solar-wind velocity forecast 24 hours ahead of72-hour forecast volume using the extant solar-wind model.forecast. In-situ data have been the primary measurements available for study of solar-wind

  15. Fitting and forecasting non-linear coupled dark energy

    E-Print Network [OSTI]

    Casas, Santiago; Baldi, Marco; Pettorino, Valeria; Vollmer, Adrian

    2015-01-01

    We consider cosmological models in which dark matter feels a fifth force mediated by the dark energy scalar field, also known as coupled dark energy. Our interest resides in estimating forecasts for future surveys like Euclid when we take into account non-linear effects, relying on new fitting functions that reproduce the non-linear matter power spectrum obtained from N-body simulations. We obtain fitting functions for models in which the dark matter-dark energy coupling is constant. Their validity is demonstrated for all available simulations in the redshift range $z=0-1.6$ and wave modes below $k=10 \\text{h/Mpc}$. These fitting formulas can be used to test the predictions of the model in the non-linear regime without the need for additional computing-intensive N-body simulations. We then use these fitting functions to perform forecasts on the constraining power that future galaxy-redshift surveys like Euclid will have on the coupling parameter, using the Fisher matrix method for galaxy clustering (GC) and w...

  16. A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy

    SciTech Connect (OSTI)

    Mellit, Adel; Pavan, Alessandro Massi

    2010-05-15

    Forecasting of solar irradiance is in general significant for planning the operations of power plants which convert renewable energies into electricity. In particular, the possibility to predict the solar irradiance (up to 24 h or even more) can became - with reference to the Grid Connected Photovoltaic Plants (GCPV) - fundamental in making power dispatching plans and - with reference to stand alone and hybrid systems - also a useful reference for improving the control algorithms of charge controllers. In this paper, a practical method for solar irradiance forecast using artificial neural network (ANN) is presented. The proposed Multilayer Perceptron MLP-model makes it possible to forecast the solar irradiance on a base of 24 h using the present values of the mean daily solar irradiance and air temperature. An experimental database of solar irradiance and air temperature data (from July 1st 2008 to May 23rd 2009 and from November 23rd 2009 to January 24th 2010) has been used. The database has been collected in Trieste (latitude 45 40'N, longitude 13 46'E), Italy. In order to check the generalization capability of the MLP-forecaster, a K-fold cross-validation was carried out. The results indicate that the proposed model performs well, while the correlation coefficient is in the range 98-99% for sunny days and 94-96% for cloudy days. As an application, the comparison between the forecasted one and the energy produced by the GCPV plant installed on the rooftop of the municipality of Trieste shows the goodness of the proposed model. (author)

  17. Short-Term Load Forecasting by Feed-Forward Neural Networks Saied S. Sharif1

    E-Print Network [OSTI]

    Taylor, James H.

    , Department of Electrical and Computer Engineering, University of New Brunswick, Fredericton, NB, CANADA, E3B) is presented for the hourly load forecasting of the coming days. In this approach, 24 independent networks are used for the next day load forecast. Each network is utilized for the prediction of load at a specific

  18. 6.9 A NEW APPROACH TO FIRE WEATHER FORECASTING AT THE TULSA WFO

    E-Print Network [OSTI]

    6.9 A NEW APPROACH TO FIRE WEATHER FORECASTING AT THE TULSA WFO Sarah J. Taylor* and Eric D. Howieson NOAA/National Weather Service Tulsa, Oklahoma 1. INTRODUCTION The modernization of the National then providesthemeteorologistanopportunitytoadjustmodel forecasts for local biases and terrain effects. The Tulsa, Oklahoma WFO has been a test office

  19. FORECASTING EMPLOYMENT & POPULATION IN TEXAS: An Investigation on TELUM Requirements, Assumptions, and Results, including a Study

    E-Print Network [OSTI]

    Kockelman, Kara M.

    -convex, non-linear optimization problem, which maximizes the entropy and thus the likelihood of the data and then compared with the district-based forecasts. The comparison showed some stark differences. For example distribution of low income households in Austin was completely different for district- and TAZ-based forecasts

  20. MM5 Contrail Forecasting in Alaska Martin Stuefer, Xiande Meng and Gerd Wendler

    E-Print Network [OSTI]

    Stuefer, Martin

    MM5 Contrail Forecasting in Alaska Martin Stuefer, Xiande Meng and Gerd Wendler Geophysical Institute, University of Alaska, Fairbanks 1. Abstract Fifth-generation mesoscale model (MM5) is being used air. Algorithm input data are MM5 forecasted temperature and humidity values at defined pressure

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

    E-Print Network [OSTI]

    Boyer, Edmond

    1 Next Generation Short-Term Forecasting of Wind Power ­ Overview of the ANEMOS Project. G outperform current state-of-the-art methods, for onshore and offshore wind power forecasting. Advanced and evaluation at a local, regional and national scale. Finally, the project demonstrates the value of wind

  2. Forecasting the Growth of Green Power Markets in the United States

    E-Print Network [OSTI]

    Forecasting the Growth of Green Power Markets in the United States October 2001 · NREL/TP-620-99-GO10337 October 2001 · NREL/TP-620-30101 · LBNL-48611 Forecasting the Growth of Green Power Markets, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any

  3. 1 Ozone pollution forecasting 3 Herve Cardot, Christophe Crambes and Pascal Sarda.

    E-Print Network [OSTI]

    Crambes, Christophe

    Contents 1 Ozone pollution forecasting 3 Herv´e Cardot, Christophe Crambes and Pascal Sarda. 1;1 Ozone pollution forecasting using conditional mean and conditional quantiles with functional covariates Herv´e Cardot, Christophe Crambes and Pascal Sarda. 1.1 Introduction Prediction of Ozone pollution

  4. FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2014

    E-Print Network [OSTI]

    Connors, Daniel A.

    1 FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2014 We are higher than normal, and vertical wind shear throughout the Atlantic basin has been much stronger than-period average values. (as of 31 July 2014) By Philip J. Klotzbach1 and William M. Gray2 This forecast as well

  5. Forecast of solar ejecta arrival at 1 AU from radial speed S. Dasso1,2

    E-Print Network [OSTI]

    Dasso, Sergio

    Forecast of solar ejecta arrival at 1 AU from radial speed S. Dasso1,2 , N. Gopalswamy1 and A. Lara of the major requirements to forecast the space weather conditions in the terrestrial envi- ronment. Several properties, such as the background solar wind speed, and the density of the ejecta. However, only a few

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

    E-Print Network [OSTI]

    Sitnov, Mikhail I.

    Global and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting issue. This paper presents a data-derived model of the solar wind-magnetosphere coupling that combines of solar wind-magnetosphere coupling: From modeling to forecasting, Geophys. Res. Lett., 31, L08802, doi:10

  7. Continuous Motion Planning for Information Forecast Han-Lim Choi and Jonathan P. How

    E-Print Network [OSTI]

    Continuous Motion Planning for Information Forecast Han-Lim Choi and Jonathan P. How Abstract-- This paper addresses planning of continuous paths for mobile sensors to improve long-term forecast of the process noise. Utilizing the spatial interpolation technique to relate the sensor movement

  8. Employment Forecasts for Ohio's Primary Metals Manufacturing and Administrative and Support Services Industries

    E-Print Network [OSTI]

    Illinois at Chicago, University of

    that are outperforming the industry average. Additional research shows that the industry is reactive to manufacturingEmployment Forecasts for Ohio's Primary Metals Manufacturing and Administrative and Support, the primary metals manufacturing industry (NAICS 331000) employment in Ohio is forecasted to decline by 21

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

    E-Print Network [OSTI]

    Genton, Marc G.

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

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

    E-Print Network [OSTI]

    Mallet, Vivien

    Ensemble-based air quality forecasts: A multimodel approach applied to ozone Vivien Mallet1 21 September 2006. [1] The potential of ensemble techniques to improve ozone forecasts ozone-monitoring networks. We found that several linear combinations of models have the potential

  11. Hourly Temperature Forecasting Using Abductive Networks R. E. Abdel-Aal

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Review Copy 1 Hourly Temperature Forecasting Using Abductive Networks R. E. Abdel-Aal Center temperatures, Artificial intelligence. Dr. R. E. Abdel-Aal, P. O. Box 1759, KFUPM, Dhahran 31261 Saudi Arabia e; Khotanzad, Afkhami-Rohani & Maratukulam, 1998; Sharif & Taylor, 2000; Xu & Chen, 1999). Such forecasts

  12. Biennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts

    E-Print Network [OSTI]

    Biennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts Electricity prices in the Council's Power Plan are forecast using the AURORATM Electricity Market Model of the entire prices at several pricing points in the West, four of which are in the Pacific Northwest. The one most

  13. Tiree Energy Pulse: Exploring Renewable Energy Forecasts on the Edge of the Grid

    E-Print Network [OSTI]

    MacDonald, Mark

    Tiree Energy Pulse: Exploring Renewable Energy Forecasts on the Edge of the Grid Will Simm1 , Maria energy consumption with supply, and together built a prototype renewable energy forecast display. A num local renewable energy was expected to be available, despite having no financial in- centive to do so

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

    E-Print Network [OSTI]

    Hwang, Kai

    peak demand periods using pricing incentives. Reliable building energy forecast models can help predictImproving Energy Use Forecast for Campus Micro-grids using Indirect Indicators Saima Aman prasanna@usc.edu Abstract--The rising global demand for energy is best addressed by adopting and promoting

  15. DEGREE DAYS AND WEATHER NOTES Weather Forecast: Chance of showers and storms through

    E-Print Network [OSTI]

    Isaacs, Rufus

    1 DEGREE DAYS AND WEATHER NOTES Weather Forecast: Chance of showers and storms through Thursday by ~225. Complete weather summaries and forecasts are at available enviroweather.msu.edu GDD (from March 1.isaacslab.ent.msu.edu/blueberryscout/blueberryscout.htm Contents · Crop Stages · Weather Notes · Disease Update · Scouting the Major Diseases of Highbush

  16. NH13A: No-source tsunami forecasting for Alaska communities

    E-Print Network [OSTI]

    Tolkova, Elena

    NH13A: No-source tsunami forecasting for Alaska communities Dmitry Nicolsky (UAF) djnicolsky://nctr.pmel.noaa.gov/ Wave trains to Alaska: direction structure (time history) tsunami source R E S P and accurate regional tsunami forecasts · A deep-ocean detector and a coastal site can be connected

  17. Towards Long-lead Forecasting of Extreme Flood Events: A Data Mining Framework for Precipitation Cluster

    E-Print Network [OSTI]

    Ding, Wei

    Towards Long-lead Forecasting of Extreme Flood Events: A Data Mining Framework for Precipitation of precipitation events occurring over from several days to several weeks. Though precise short- term forecasting of precipitation clusters can be attempted by identifying persistent atmospheric regimes that are conducive

  18. Extendedrange seasonal hurricane forecasts for the North Atlantic with a hybrid dynamicalstatistical model

    E-Print Network [OSTI]

    Webster, Peter J.

    Extendedrange seasonal hurricane forecasts for the North Atlantic with a hybrid 20 September 2010; published 9 November 2010. [1] A hybrid forecast model for seasonal hurricane between the number of seasonal hurricane and the large scale variables from ECMWF hindcasts. The increase

  19. Probabilistic Precipitation Forecast Skill as a Function of Ensemble Size and Spatial Scale in a Convection-Allowing Ensemble

    E-Print Network [OSTI]

    Xue, Ming

    Probabilistic Precipitation Forecast Skill as a Function of Ensemble Size and Spatial Scale decreases. These results appear to reflect the broadening of the forecast probability distribution function lead time. They also illustrate that efficient allocation of computing resources for convection

  20. Comment on `Testing earthquake prediction methods: "The West Pacific short-term forecast of earthquakes with magnitude MwHRV >= 5.8"' by V. G. Kossobokov

    E-Print Network [OSTI]

    Kagan, Yan Y; Jackson, David D

    2006-01-01

    tensor solutions for 1087 earthquakes, Phys. Earth Planet.and time-independent earthquake forecast models for southernKagan, 1999. Testable earthquake forecasts for 1999, Seism.

  1. Load forecasting for active distribution networks Simone Paoletti, Member, IEEE, Marco Casini, Member, IEEE, Antonio Giannitrapani, Member, IEEE,

    E-Print Network [OSTI]

    Giannitrapani, Antonello

    forecasting for distribution networks with Active Demand (AD), a new concept in smart-grids introduced within

  2. Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

    Broader source: Energy.gov [DOE]

    Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

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

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01

    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.

  4. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    SciTech Connect (OSTI)

    Wong-Parodi, Gabrielle; Lekov, Alex; Dale, Larry

    2005-02-09

    This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

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

    E-Print Network [OSTI]

    Niyogi, Dev

    (GEM) for Mesoscale Weather Forecasting Applications DEV NIYOGI Department of Agronomy, and Department form 13 May 2008) ABSTRACT Current land surface schemes used for mesoscale weather forecast models use model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM

  6. J2.6 A SPATIAL DATA MINING APPROACH FOR VERIFICATION AND UNDERSTANDING OF ENSEMBLE PRECIPITATION FORECASTING

    E-Print Network [OSTI]

    Gruenwald, Le

    FORECASTING Xuechao Yu* 1,2 and Ming Xue 2,3 1 NOAA/NWS/WDTB Cooperative Institute for Mesoscale is placed on meso- scale ensemble forecasting in recent years [e.g., the Storm and Mesoscale Ensemble complicated for mesoscale quantitative precipitation forecast (QPF), since QPF is a discontinuous field. Em

  7. Variable Selection and Inference for Multi-period Forecasting Problems

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas; Timmermann, Allan

    ?t,x?t)?. Multi-period forecasts of yt can then be obtained iteratively using a conventional VAR of the form zt = µz + ( Ap(L) Bq(L) Cr(L) Ds(L) ) zt?1 + ?t, (10) where p and q are the lag order of yt and xt in the equation for yt and r and s is the lag order... , i.e. Cr(L) and Bq(L) in particular. To deal with this issue, a conditional factor-augmentation approach can be used. In this approach, the large-dimensional xt-vector is condensed into a subset of factors, fˆ t, of dimension m < M , used to summarize...

  8. The Impact of Non-Gaussianity upon Cosmological Forecasts

    E-Print Network [OSTI]

    Repp, Andrew; Carron, Julien; Wolk, Melody

    2015-01-01

    The primary science driver for 3D galaxy surveys is their potential to constrain cosmological parameters. Forecasts of these surveys' effectiveness typically assume Gaussian statistics for the underlying matter density, despite the fact that the actual distribution is decidedly non-Gaussian. To quantify the effect of this assumption, we employ an analytic expression for the power spectrum covariance matrix to calculate the Fisher information for BAO-type model surveys. We find that for typical number densities, at $k_\\mathrm{max} = 0.5 h$ Mpc$^{-1}$, Gaussian assumptions significantly overestimate the information on all parameters considered, in some cases by up to an order of magnitude. However, after marginalizing over a six-parameter set, the form of the covariance matrix (dictated by $N$-body simulations) causes the majority of the effect to shift to the "amplitude-like" parameters, leaving the others virtually unaffected. We find that Gaussian assumptions at such wavenumbers can underestimate the dark en...

  9. Information Preservation and Weather Forecasting for Black Holes

    E-Print Network [OSTI]

    S. W. Hawking

    2014-01-22

    It has been suggested [1] that the resolution of the information paradox for evaporating black holes is that the holes are surrounded by firewalls, bolts of outgoing radiation that would destroy any infalling observer. Such firewalls would break the CPT invariance of quantum gravity and seem to be ruled out on other grounds. A different resolution of the paradox is proposed, namely that gravitational collapse produces apparent horizons but no event horizons behind which information is lost. This proposal is supported by ADS-CFT and is the only resolution of the paradox compatible with CPT. The collapse to form a black hole will in general be chaotic and the dual CFT on the boundary of ADS will be turbulent. Thus, like weather forecasting on Earth, information will effectively be lost, although there would be no loss of unitarity.

  10. Residential applliance data, assumptions and methodology for end-use forecasting with EPRI-REEPS 2.1

    SciTech Connect (OSTI)

    Hwang, R.J,; Johnson, F.X.; Brown, R.E.; Hanford, J.W.; Kommey, J.G.

    1994-05-01

    This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the US residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute. In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70% of electricity consumption and 30% of natural gas consumption in the US residential sector. Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific technologies within those end-uses, developing cost data for the various technologies, and specifying decision models to forecast future purchase decisions by households. Our implementation of the REEPS 2.1 modeling framework draws on the extensive technology, cost and market data assembled by LBL for the purpose of analyzing federal energy conservation standards. The resulting residential appliance forecasting model offers a flexible and accurate tool for analyzing the effect of policies at the national level.

  11. Observational Analysis of the Predictability of Mesoscale Convective Systems ISRAEL L. JIRAK AND WILLIAM R. COTTON

    E-Print Network [OSTI]

    Observational Analysis of the Predictability of Mesoscale Convective Systems ISRAEL L. JIRAK (Manuscript received 30 December 2005, in final form 4 October 2006) ABSTRACT Mesoscale convective systems of usefulness in operational forecasting. 1. Introduction Mesoscale convective systems (MCSs) frequently de

  12. The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant.

    SciTech Connect (OSTI)

    Martin Wilde, Principal Investigator

    2012-12-31

    ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most wind plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational setting. It shall be demonstrated that when used properly, the real-time offsite measurements materially improve wind ramp capture and prediction statistics, when compared to traditional wind forecasting techniques and to a simple persistence model.

  13. Machine Learning Enhancement of Storm-Scale Ensemble Probabilistic Quantitative Precipitation Forecasts

    E-Print Network [OSTI]

    Xue, Ming

    Machine Learning Enhancement of Storm-Scale Ensemble Probabilistic Quantitative Precipitation uncertainty. Machine learning methods can produce calibrated probabilistic forecasts from the raw ensemble and machine learning are working to address these challenges. Numerical weather prediction (NWP) models

  14. Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting Technology

    Broader source: Energy.gov [DOE]

    As part of this project, new solar forecasting technology will be developed that leverages big data processing, deep machine learning, and cloud modeling integrated in a universal platform with an...

  15. The Peloton Approach : forecasting and strategic planning for emerging technologies : a case for RFID

    E-Print Network [OSTI]

    Thuvara, Vineet

    2006-01-01

    The RFID industry is going through a sea of change and at different levels within the industry. Forecasts have been done on different facets of the RFID/EPC industry like the market size or the possible financial returns. ...

  16. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    and validation.   Solar Energy.   73:5, 307? Perez, R. , irradiance forecasts for solar energy applications based on using satellite data.   Solar Energy 67:1?3, 139?150.  

  17. An adaptive nonlinear MOS scheme for precipitation forecasts using neural networks

    E-Print Network [OSTI]

    Hsieh, William

    An adaptive nonlinear MOS scheme for precipitation forecasts using neural networks Yuval, William W A novel neural network (NN) based scheme performs nonlinear Model Output Statistics (MOS) for generating

  18. Time Series Methods for ForecastingElectricityMarket Pricing Zoran Obradovic Kevin Tomsovic

    E-Print Network [OSTI]

    Obradovic, Zoran

    of traditional commodities, such as,oil or agricultural products. Clearly, assessing the effectivenessTime Series Methods for ForecastingElectricityMarket Pricing Zoran Obradovic Kevin Tomsovic PO Box

  19. Testing long-term earthquake forecasts: likelihood methods and error diagrams

    E-Print Network [OSTI]

    Kagan, Yan Y

    2009-01-01

    Jackson, 1991. Long-term earthquake clustering, Geophys. J.forecast- ing of earthquakes, J. geophys. Res. , 99(B7),G. M. & Y. Y. Kagan, 1992. Earthquake prediction and its

  20. Forecasting the S&P 500 index using time series analysis and simulation methods

    E-Print Network [OSTI]

    Chan, Eric Glenn

    2009-01-01

    The S&P 500 represents a diverse pool of securities in addition to Large Caps. A range of audiences are interested in the S&P 500 forecasts including investors, speculators, economists, government and researchers. The ...

  1. Integration of Behind-the-Meter PV Fleet Forecasts into Utility...

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

    the spatial and temporal resolution of SolarAnywhere, an online satellite-based irradiance dataset, and adding output variability and PV performance forecasts to the Web-based...

  2. Examining Information Entropy Approaches as Wind Power Forecasting Performance Metrics: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Orwig, K.; Milligan, M.

    2012-06-01

    In this paper, we examine the parameters associated with the calculation of the Renyi entropy in order to further the understanding of its application to assessing wind power forecasting errors.

  3. Freeway Short-Term Traffic Flow Forecasting by Considering Traffic Volatility Dynamics and Missing Data Situations 

    E-Print Network [OSTI]

    Zhang, Yanru

    2012-10-19

    traffic managers in seeking solutions to congestion problems on urban freeways and surface streets. There is new research interest in short-term traffic flow forecasting due to recent developments in ITS technologies. Previous research involves...

  4. Reverse supply chain forecasting and decision modeling for improved inventory management

    E-Print Network [OSTI]

    Petersen, Brian J. (Brian Jude)

    2013-01-01

    This thesis details research performed during a six-month engagement with Verizon Wireless (VzW) in the latter half of 2012. The key outcomes are a forecasting model and decision-support framework to improve management of ...

  5. Price forecasting for U.S. cattle feeders: which technique to apply? 

    E-Print Network [OSTI]

    Hicks, Geoff Cody

    1997-01-01

    the following:1. FAPRI3. AO S5. Univariate Time Series7. Composite 2. WASDE4. Futures Market6. Multivariate Time Series The characteristics of each of the aforementioned forecast techniques are explained within the appropriate chapter. Furthermore, it should...

  6. Radar-Derived Forecasts of Cloud-to-Ground Lightning Over Houston, Texas 

    E-Print Network [OSTI]

    Mosier, Richard Matthew

    2011-02-22

    -derived Products....26 1.6 Thesis Objectives and Hypothesis...........................................................................27 2. DATA AND METHODOLOGY..................................................................................29 2.1 Radar............................................................................................42 2.4.4 Storm Cell Position Forecast............................................................................44 2.5 Lightning Correlation..............................................................................................45 2.6 CG...

  7. Comparative forecasting performance of symmetric and asymmetric conditional volatility models of an exchange rate. 

    E-Print Network [OSTI]

    Balaban, Ercan

    2002-01-01

    The relative out-of-sample forecasting quality of symmetric and asymmetric conditional volatility models of an exchange rate differs according to the symmetric and asymmetric evaluation criteria as well as a regression-based ...

  8. Comparison of Various Deterministic Forecasting Techniques in Shale Gas Reservoirs with Emphasis on the Duong Method 

    E-Print Network [OSTI]

    Joshi, Krunal Jaykant

    2012-10-19

    There is a huge demand in the industry to forecast production in shale gas reservoirs accurately. There are many methods including volumetric, Decline Curve Analysis (DCA), analytical simulation and numerical simulation. Each one of these methods...

  9. FireGrid: Forecasting Fire Dynamics to Lead the Emergency Response 

    E-Print Network [OSTI]

    Rein, Guillermo

    2007-06-19

    The predictions of future events has fascinated humanity since the beginning of history. This attraction has permeated into science and engineering, where several disciplines has emerged providing the capability to forecast ...

  10. The Potential for Integrating GIS in Activity-Based Forecasting Models

    E-Print Network [OSTI]

    McNally, Michael G.

    1997-01-01

    3" (ENTERTAINMENT) Figure 4. A GIS-based Microsimulation ofDestinations Figure 5. A GIS-based Microsimulation ofPotential for Integrating GIS in Activity Based Forecasting

  11. Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets

    E-Print Network [OSTI]

    Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

    2005-01-01

    index.html. Appendix A.1 Natural Gas Price Data for FuturesError STEO Error A.1 Natural Gas Price Data for Futuresof forecasts for natural gas prices as reported by the

  12. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    transport and  numerical weather modeling.   J.  Applied cross correlations.    Weather and Forecasting, 8:4, 401?of radiation for numerical weather prediction and climate 

  13. Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk 

    E-Print Network [OSTI]

    Kim, Seong D.

    2010-07-14

    Hurricane Katrina of 2005 was responsible for at least 81 billion dollars of property damage. In planning for such emergencies, society must decide whether to invest in the ability to evacuate more speedily or in improved forecasting technology...

  14. Developing a framework for dependable demand forecasts in the consumer packaged goods industry

    E-Print Network [OSTI]

    Uriarte, Daniel Antonio

    2010-01-01

    As a consumer packaged goods company, "Company X" manufactures products "make-to-stock"; therefore, having reliable demand forecasts is fundamental for successful planning and execution. Not isolated to "Company X" or to ...

  15. Performances of an experimental platform dedicated to European pollution forecast based on the CHIMERE

    E-Print Network [OSTI]

    Menut, Laurent

    Performances of an experimental platform dedicated to European pollution forecast based du Climat et de l'Environnement - LSCE/IPSL The GEMS european project is dedicated to the definition

  16. Using multi-layer models to forecast gas flow rates in tight gas reservoirs 

    E-Print Network [OSTI]

    Jerez Vera, Sergio Armando

    2007-04-25

    USING MULTI-LAYER MODELS TO FORECAST GAS FLOW RATES IN TIGHT GAS RESERVOIRS A Thesis by SERGIO ARMANDO JEREZ VERA Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE December 2006 Major Subject: Petroleum Engineering USING MULTI-LAYER MODELS TO FORECAST GAS FLOW RATES IN TIGHT GAS RESERVOIRS A Thesis by SERGIO ARMANDO JEREZ VERA Submitted...

  17. U.S. Department of Energy Workshop Report: Solar Resources and Forecasting

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01

    This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

  18. Forecasting stock market returns over multiple time horizons

    E-Print Network [OSTI]

    Kroujiline, Dimitri; Ushanov, Dmitry; Sharov, Sergey V; Govorkov, Boris

    2015-01-01

    In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we further develop the news-driven analytic model of the stock market derived in Gusev et al. (2015). This enables us to capture market dynamics at various timescales and shed light on mechanisms underlying certain market behaviors such as transitions between bull- and bear markets and the self-similar behavior of price changes. We investigate the model and show that the market is nearly efficient on timescales shorter than one day, adjusting quickly to incoming news, but is inefficient on longer timescales, where news may have a long-lasting nonlinear impact on dynamics attributable to a feedback mechanism acting over these horizons. Using the model, we design the prototypes of algorithmic strategies that utilize news flow, quantified and measured, as the only input to trade on market return forecasts over multiple horizons, from days to months. The backtested res...

  19. Natural Priors, CMSSM Fits and LHC Weather Forecasts

    E-Print Network [OSTI]

    Ben C Allanach; Kyle Cranmer; Christopher G Lester; Arne M Weber

    2007-07-05

    Previous LHC forecasts for the constrained minimal supersymmetric standard model (CMSSM), based on current astrophysical and laboratory measurements, have used priors that are flat in the parameter tan beta, while being constrained to postdict the central experimental value of MZ. We construct a different, new and more natural prior with a measure in mu and B (the more fundamental MSSM parameters from which tan beta and MZ are actually derived). We find that as a consequence this choice leads to a well defined fine-tuning measure in the parameter space. We investigate the effect of such on global CMSSM fits to indirect constraints, providing posterior probability distributions for Large Hadron Collider (LHC) sparticle production cross sections. The change in priors has a significant effect, strongly suppressing the pseudoscalar Higgs boson dark matter annihilation region, and diminishing the probable values of sparticle masses. We also show how to interpret fit information from a Markov Chain Monte Carlo in a frequentist fashion; namely by using the profile likelihood. Bayesian and frequentist interpretations of CMSSM fits are compared and contrasted.

  20. Bases for solid waste volume estimates for tank waste remediation system

    SciTech Connect (OSTI)

    Reddick, G.W., Westinghouse Hanford

    1996-08-01

    This document presents the background and basis for the Tank Waste Remediation System forecast for solid waste submitted in June 1996. The forecast was generated for single-shell tank and double-shell tank activities including operations through retrieval and disposal of chemical tank waste.