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Title: Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry

Abstract

Around the world wind energy is starting to become a major energy provider in electricity markets, as well as participating in ancillary services markets to help maintain grid stability. The reliability of system operations and smooth integration of wind energy into electricity markets has been strongly supported by years of improvement in weather and wind power forecasting systems. Deterministic forecasts are still predominant in utility practice although truly optimal decisions and risk hedging are only possible with the adoption of uncertainty forecasts. One of the main barriers for the industrial adoption of uncertainty forecasts is the lack of understanding of its information content (e.g., its physical and statistical modeling) and standardization of uncertainty forecast products, which frequently leads to mistrust towards uncertainty forecasts and their applicability in practice. Our paper aims at improving this understanding by establishing a common terminology and reviewing the methods to determine, estimate, and communicate the uncertainty in weather and wind power forecasts. This conceptual analysis of the state of the art highlights that: (i) end-users should start to look at the forecast's properties in order to map different uncertainty representations to specific wind energy-related user requirements; (ii) a multidisciplinary team is required to foster themore » integration of stochastic methods in the industry sector. Furthermore, a set of recommendations for standardization and improved training of operators are provided along with examples of best practices.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [9]
  1. INESC Technology and Science, Porto (Portugal)
  2. Weather & Energy PROGnoses (WEPROG), Assens (Denmark)
  3. German Weather Service, Offenbach (Germany)
  4. Fraunhofer Inst. for Wind Energy and Energy System Technology (IWES), Kasse (Germany)
  5. Univ. of Strathclyde, Glasgow (United Kingdom). Dept. of Electronic and Electrical Engineering
  6. KTH Royal Inst. of Technology, Stockholm (Sweden). Dept. of Mechanics
  7. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  8. Univ. of North Carolina, Charlotte, NC (United States). Dept. of Engineering Technology and Construction Management
  9. Mines ParisTech and PSL Research Univ., Cedex (France). . Centre for Processes, Renewable Energies and Energy Systems (PERSEE)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1399352
Report Number(s):
NREL/JA-5D00-70107
Journal ID: ISSN 1996-1073; ENERGA
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Energies
Additional Journal Information:
Journal Volume: 10; Journal Issue: 9; Journal ID: ISSN 1996-1073
Publisher:
MDPI AG
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; wind energy; uncertainty; decision-making; quantiles; ensembles; forecast; statistics; weather

Citation Formats

Bessa, Ricardo, Möhrlen, Corinna, Fundel, Vanessa, Siefert, Malte, Browell, Jethro, Haglund El Gaidi, Sebastian, Hodge, Bri-Mathias, Cali, Umit, and Kariniotakis, George. Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry. United States: N. p., 2017. Web. https://doi.org/10.3390/en10091402.
Bessa, Ricardo, Möhrlen, Corinna, Fundel, Vanessa, Siefert, Malte, Browell, Jethro, Haglund El Gaidi, Sebastian, Hodge, Bri-Mathias, Cali, Umit, & Kariniotakis, George. Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry. United States. https://doi.org/10.3390/en10091402
Bessa, Ricardo, Möhrlen, Corinna, Fundel, Vanessa, Siefert, Malte, Browell, Jethro, Haglund El Gaidi, Sebastian, Hodge, Bri-Mathias, Cali, Umit, and Kariniotakis, George. Thu . "Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry". United States. https://doi.org/10.3390/en10091402. https://www.osti.gov/servlets/purl/1399352.
@article{osti_1399352,
title = {Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry},
author = {Bessa, Ricardo and Möhrlen, Corinna and Fundel, Vanessa and Siefert, Malte and Browell, Jethro and Haglund El Gaidi, Sebastian and Hodge, Bri-Mathias and Cali, Umit and Kariniotakis, George},
abstractNote = {Around the world wind energy is starting to become a major energy provider in electricity markets, as well as participating in ancillary services markets to help maintain grid stability. The reliability of system operations and smooth integration of wind energy into electricity markets has been strongly supported by years of improvement in weather and wind power forecasting systems. Deterministic forecasts are still predominant in utility practice although truly optimal decisions and risk hedging are only possible with the adoption of uncertainty forecasts. One of the main barriers for the industrial adoption of uncertainty forecasts is the lack of understanding of its information content (e.g., its physical and statistical modeling) and standardization of uncertainty forecast products, which frequently leads to mistrust towards uncertainty forecasts and their applicability in practice. Our paper aims at improving this understanding by establishing a common terminology and reviewing the methods to determine, estimate, and communicate the uncertainty in weather and wind power forecasts. This conceptual analysis of the state of the art highlights that: (i) end-users should start to look at the forecast's properties in order to map different uncertainty representations to specific wind energy-related user requirements; (ii) a multidisciplinary team is required to foster the integration of stochastic methods in the industry sector. Furthermore, a set of recommendations for standardization and improved training of operators are provided along with examples of best practices.},
doi = {10.3390/en10091402},
journal = {Energies},
number = 9,
volume = 10,
place = {United States},
year = {2017},
month = {9}
}

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Works referenced in this record:

Opportunity Cost Bidding by Wind Generators in Forward Markets: Analytical Results
journal, August 2011

  • Dent, Chris J.; Bialek, Janusz W.; Hobbs, Benjamin F.
  • IEEE Transactions on Power Systems, Vol. 26, Issue 3
  • DOI: 10.1109/TPWRS.2010.2100412

Probability or frequency? Expressing forecast uncertainty in public weather forecasts
journal, September 2009

  • Joslyn, Susan L.; Nichols, Rebecca M.
  • Meteorological Applications, Vol. 16, Issue 3
  • DOI: 10.1002/met.121

Multimodel Ensemble Forecasts for Weather and Seasonal Climate
journal, December 2000


Untersuchung verschiedener Handelsstrategien für Wind- und Solarenergie unter Berücksichtigung der EEG 2012 Novellierung
journal, November 2011

  • Möhrlen, Corinna; Pahlow, Markus; Jørgensen, Jess U.
  • Zeitschrift für Energiewirtschaft, Vol. 36, Issue 1
  • DOI: 10.1007/s12398-011-0071-z

Kalman Filter and Analog Schemes to Postprocess Numerical Weather Predictions
journal, November 2011

  • Delle Monache, Luca; Nipen, Thomas; Liu, Yubao
  • Monthly Weather Review, Vol. 139, Issue 11
  • DOI: 10.1175/2011MWR3653.1

Active Distribution Grid Management Based on Robust AC Optimal Power Flow
journal, November 2018

  • Soares, Tiago; Bessa, Ricardo J.; Pinson, Pierre
  • IEEE Transactions on Smart Grid, Vol. 9, Issue 6
  • DOI: 10.1109/TSG.2017.2707065

Path forecast evaluation
journal, March 2010

  • Jordà, Òscar; Marcellino, Massimiliano
  • Journal of Applied Econometrics, Vol. 25, Issue 4
  • DOI: 10.1002/jae.1166

Impact of Surface Parameter Uncertainties within the Canadian Regional Ensemble Prediction System
journal, May 2013

  • Lavaysse, Christophe; Carrera, Marco; Bélair, Stéphane
  • Monthly Weather Review, Vol. 141, Issue 5
  • DOI: 10.1175/MWR-D-11-00354.1

Using quantile regression to extend an existing wind power forecasting system with probabilistic forecasts
journal, January 2006

  • Nielsen, Henrik Aalborg; Madsen, Henrik; Nielsen, Torben Skov
  • Wind Energy, Vol. 9, Issue 1-2
  • DOI: 10.1002/we.180

Transforming climate model output to forecasts of wind power production: how much resolution is enough?: Transforming climate model output to wind power forecasts
journal, July 2017

  • MacLeod, Dave; Torralba, Verónica; Davis, Melanie
  • Meteorological Applications, Vol. 25, Issue 1
  • DOI: 10.1002/met.1660

Evaluating the quality of scenarios of short-term wind power generation
journal, August 2012


Review of the Ensemble Kalman Filter for Atmospheric Data Assimilation
journal, December 2016


Review on probabilistic forecasting of wind power generation
journal, April 2014


Well-Being Analysis for Composite Generation and Transmission Systems
journal, November 2004

  • daSilva, A. M. L.; deResende, L. C.; daFonsecaManso, L. A.
  • IEEE Transactions on Power Systems, Vol. 19, Issue 4
  • DOI: 10.1109/TPWRS.2004.835633

Stochastic dynamic prediction
journal, January 1969


‘Good’ or ‘bad’ wind power forecasts: a relative concept
journal, December 2010

  • Bessa, R. J.; Miranda, V.; Botterud, A.
  • Wind Energy, Vol. 14, Issue 5
  • DOI: 10.1002/we.444

Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power
journal, August 2007

  • Pinson, Pierre; Chevallier, Christophe; Kariniotakis, George N.
  • IEEE Transactions on Power Systems, Vol. 22, Issue 3
  • DOI: 10.1109/TPWRS.2007.901117

Ensemble Forecasting at NCEP and the Breeding Method
journal, December 1997


Aspects of structural health and condition monitoring of offshore wind turbines
journal, February 2015

  • Antoniadou, I.; Dervilis, N.; Papatheou, E.
  • Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 373, Issue 2035
  • DOI: 10.1098/rsta.2014.0075

Skill forecasting from ensemble predictions of wind power
journal, July 2009


A local ensemble Kalman filter for atmospheric data assimilation
journal, January 2004

  • Ott, Edward; Hunt, Brian R.; Szunyogh, Istvan
  • Tellus A: Dynamic Meteorology and Oceanography, Vol. 56, Issue 5
  • DOI: 10.3402/tellusa.v56i5.14462

Communicating forecast uncertainty: public perception of weather forecast uncertainty
journal, April 2010

  • Joslyn, Susan; Savelli, Sonia
  • Meteorological Applications, Vol. 17, Issue 2
  • DOI: 10.1002/met.190

Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds
journal, July 2008


Using Bayesian Model Averaging to Calibrate Forecast Ensembles
journal, May 2005

  • Raftery, Adrian E.; Gneiting, Tilmann; Balabdaoui, Fadoua
  • Monthly Weather Review, Vol. 133, Issue 5, p. 1155-1174
  • DOI: 10.1175/MWR2906.1

The effects of land surface process perturbations in a global ensemble forecast system
journal, September 2016


Simultaneous Prediction Intervals
journal, May 1968


Correlations and Copulas for Decision and Risk Analysis
journal, February 1999


Singular Vector Structure and Evolution of a Recurving Tropical Cyclone
journal, February 2009


Ensemble Model Output Statistics for Wind Vectors
journal, October 2012

  • Schuhen, Nina; Thorarinsdottir, Thordis L.; Gneiting, Tilmann
  • Monthly Weather Review, Vol. 140, Issue 10
  • DOI: 10.1175/MWR-D-12-00028.1

Generation of Scenarios from Calibrated Ensemble Forecasts with a Dual-Ensemble Copula-Coupling Approach
journal, November 2016

  • Ben Bouallègue, Zied; Heppelmann, Tobias; Theis, Susanne E.
  • Monthly Weather Review, Vol. 144, Issue 12
  • DOI: 10.1175/MWR-D-15-0403.1

Very-Short-Term Probabilistic Wind Power Forecasts by Sparse Vector Autoregression
journal, January 2015


The Use of Model Output Statistics (MOS) in Objective Weather Forecasting
journal, December 1972


Scenarios and Policy Aggregation in Optimization Under Uncertainty
journal, February 1991

  • Rockafellar, R. T.; Wets, Roger J. -B.
  • Mathematics of Operations Research, Vol. 16, Issue 1
  • DOI: 10.1287/moor.16.1.119

Flow-dependent predictability of the North Atlantic jet: PREDICTABILITY OF NORTH ATLANTIC JET
journal, May 2013

  • Frame, T. H. A.; Methven, J.; Gray, S. L.
  • Geophysical Research Letters, Vol. 40, Issue 10
  • DOI: 10.1002/grl.50454

Probabilistic Forecasts of Wind Power Generation by Stochastic Differential Equation Models: Probabilistic Forecasts of Wind Power Generation
journal, February 2016

  • Møller, Jan Kloppenborg; Zugno, Marco; Madsen, Henrik
  • Journal of Forecasting, Vol. 35, Issue 3
  • DOI: 10.1002/for.2367

The ECMWF Ensemble Prediction System: Methodology and validation
journal, January 1996

  • Molteni, F.; Buizza, R.; Palmer, T. N.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 122, Issue 529
  • DOI: 10.1002/qj.49712252905

Multivariate ensemble Model Output Statistics using empirical copulas: Multivariate Ensemble MOS using Empirical Copulas
journal, August 2014

  • Wilks, Daniel S.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 141, Issue 688
  • DOI: 10.1002/qj.2414

Uncertainty Quantification in Complex Simulation Models Using Ensemble Copula Coupling
journal, November 2013

  • Schefzik, Roman; Thorarinsdottir, Thordis L.; Gneiting, Tilmann
  • Statistical Science, Vol. 28, Issue 4
  • DOI: 10.1214/13-STS443

Methodologies to Determine Operating Reserves Due to Increased Wind Power
journal, October 2012

  • Holttinen, Hannele; Milligan, Michael; Ela, Erik
  • IEEE Transactions on Sustainable Energy, Vol. 3, Issue 4
  • DOI: 10.1109/TSTE.2012.2208207

An Adaptive Ensemble Kalman Filter
journal, January 2000


Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Reforecasts. Part I: Two-Meter Temperatures
journal, July 2008

  • Hagedorn, Renate; Hamill, Thomas M.; Whitaker, Jeffrey S.
  • Monthly Weather Review, Vol. 136, Issue 7
  • DOI: 10.1175/2007MWR2410.1

Ensemble-based probabilistic forecasting at Horns Rev
journal, March 2009

  • Pinson, Pierre; Madsen, Henrik
  • Wind Energy, Vol. 12, Issue 2
  • DOI: 10.1002/we.309

Variogram-Based Proper Scoring Rules for Probabilistic Forecasts of Multivariate Quantities*
journal, April 2015


Quantifying Risk of Wind Power Ramps in ERCOT
journal, November 2017


Quantile Forecasting of Wind Power Using Variability Indices
journal, February 2013

  • Anastasiades, Georgios; McSharry, Patrick
  • Energies, Vol. 6, Issue 2
  • DOI: 10.3390/en6020662

The Schaake Shuffle: A Method for Reconstructing Space–Time Variability in Forecasted Precipitation and Temperature Fields
journal, February 2004


The Conditional Distribution of Excess Returns: An Empirical Analysis
journal, June 1995


Common Mistakes in Making Value Trade-Offs
journal, December 2002


Probabilistic gradient boosting machines for GEFCom2014 wind forecasting
journal, July 2016


Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond
journal, July 2016


Roots of Ensemble Forecasting
journal, July 2005


Probabilistic wind speed forecasting on a grid based on ensemble model output statistics
journal, September 2015

  • Scheuerer, Michael; Möller, David
  • The Annals of Applied Statistics, Vol. 9, Issue 3
  • DOI: 10.1214/15-AOAS843

Bootstrap Prediction Intervals for Regression
journal, December 1985


Statistical Analysis of Wind Power Forecast Error
journal, August 2008

  • Bludszuweit, H.; Dominguez-Navarro, J. A.; Llombart, A.
  • IEEE Transactions on Power Systems, Vol. 23, Issue 3
  • DOI: 10.1109/TPWRS.2008.922526

Handling renewable energy variability and uncertainty in power systems operation: Handling renewable energy variability and uncertainty in power systems operation
journal, February 2013

  • Bessa, Ricardo; Moreira, Carlos; Silva, Bernardo
  • Wiley Interdisciplinary Reviews: Energy and Environment, Vol. 3, Issue 2
  • DOI: 10.1002/wene.76

Ensemble Reforecasting: Improving Medium-Range Forecast Skill Using Retrospective Forecasts
journal, June 2004


Uncertainty forecasts improve weather-related decisions and attenuate the effects of forecast error.
journal, January 2012

  • Joslyn, Susan L.; LeClerc, Jared E.
  • Journal of Experimental Psychology: Applied, Vol. 18, Issue 1
  • DOI: 10.1037/a0025185

Market protocols in ERCOT and their effect on wind generation
journal, July 2010


The Cry Wolf Effect and Weather-Related Decision Making: Crying Wolf and Weather-Related Decision Making
journal, January 2015


A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation
journal, January 2001


The Ensemble Kalman Filter: theoretical formulation and practical implementation
journal, November 2003


Limited-Area Ensemble-Based Data Assimilation
journal, July 2011


Critical review of recent advances and further developments needed in AC optimal power flow
journal, July 2016


Very-short-term probabilistic forecasting of wind power with generalized logit-normal distributions
journal, February 2012


Reserve Setting and Steady-State Security Assessment Using Wind Power Uncertainty Forecast: A Case Study
journal, October 2012

  • Bessa, Ricardo J.; Matos, Manuel A.; Costa, Ivo C.
  • IEEE Transactions on Sustainable Energy, Vol. 3, Issue 4
  • DOI: 10.1109/TSTE.2012.2199340

The Effect of Uncertainty Visualizations on Decision Making in Weather Forecasting
journal, March 2008

  • Nadav-Greenberg, Limor; Joslyn, Susan L.; Taing, Meng U.
  • Journal of Cognitive Engineering and Decision Making, Vol. 2, Issue 1
  • DOI: 10.1518/155534308X284354

Long Waves and Cyclone Waves
journal, January 1949


Evaluating Quantile Assessments
journal, October 2009

  • Jose, Victor Richmond R.; Winkler, Robert L.
  • Operations Research, Vol. 57, Issue 5
  • DOI: 10.1287/opre.1080.0665

Computation of Dynamic Operating Balancing Reserve for Wind Power Integration for the Time-Horizon 1–48 Hours
journal, October 2012

  • Menemenlis, Nickie; Huneault, Maurice; Robitaille, Andre
  • IEEE Transactions on Sustainable Energy, Vol. 3, Issue 4
  • DOI: 10.1109/TSTE.2011.2181878

Influence of extreme weather and climate change on the resilience of power systems: Impacts and possible mitigation strategies
journal, October 2015


Singular vectors in atmospheric sciences: A review
journal, July 2012


State Forecasting and Operational Planning for Distribution Network Energy Management Systems
journal, March 2016

  • Hayes, Barry Patrick; Prodanovic, Milan
  • IEEE Transactions on Smart Grid, Vol. 7, Issue 2
  • DOI: 10.1109/TSG.2015.2489700

Wind power forecasting uncertainty and unit commitment
journal, November 2011


Setting the Operating Reserve Using Probabilistic Wind Power Forecasts
journal, May 2011


Extended-Range Atmospheric Prediction and the Lorenz Model
journal, January 1993


A Hybrid NWP–Analog Ensemble
journal, February 2016


Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation
journal, May 2005

  • Gneiting, Tilmann; Raftery, Adrian E.; Westveld, Anton H.
  • Monthly Weather Review, Vol. 133, Issue 5
  • DOI: 10.1175/MWR2904.1

Using Initial Condition and Model Physics Perturbations in Short-Range Ensemble Simulations of Mesoscale Convective Systems
journal, July 2000


The economic value of ensemble forecasts as a tool for risk assessment: From days to decades
journal, April 2002

  • Palmer, T. N.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 128, Issue 581
  • DOI: 10.1256/0035900021643593

Comparison of Ensemble-MOS Methods Using GFS Reforecasts
journal, June 2007

  • Wilks, Daniel S.; Hamill, Thomas M.
  • Monthly Weather Review, Vol. 135, Issue 6
  • DOI: 10.1175/MWR3402.1

A review on the recent history of wind power ramp forecasting
journal, December 2015

  • Gallego-Castillo, Cristobal; Cuerva-Tejero, Alvaro; Lopez-Garcia, Oscar
  • Renewable and Sustainable Energy Reviews, Vol. 52
  • DOI: 10.1016/j.rser.2015.07.154

Defining Risk
journal, November 2004


On-line assessment of prediction risk for wind power production forecasts
journal, April 2004

  • Pinson, P.; Kariniotakis, G.
  • Wind Energy, Vol. 7, Issue 2
  • DOI: 10.1002/we.114

Conditional Prediction Intervals of Wind Power Generation
journal, November 2010


Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics
journal, January 1994

  • Evensen, Geir
  • Journal of Geophysical Research, Vol. 99, Issue C5
  • DOI: 10.1029/94JC00572

Seasonal Climate Prediction: A New Source of Information for the Management of Wind Energy Resources
journal, May 2017

  • Torralba, Verónica; Doblas-Reyes, Francisco J.; MacLeod, Dave
  • Journal of Applied Meteorology and Climatology, Vol. 56, Issue 5
  • DOI: 10.1175/JAMC-D-16-0204.1

Estimating trajectory uncertainties due to flow dependent errors in the atmospheric analysis
journal, January 2009


Wind Power Trading Under Uncertainty in LMP Markets
journal, May 2012


NOAA's Second-Generation Global Medium-Range Ensemble Reforecast Dataset
journal, October 2013

  • Hamill, Thomas M.; Bates, Gary T.; Whitaker, Jeffrey S.
  • Bulletin of the American Meteorological Society, Vol. 94, Issue 10
  • DOI: 10.1175/BAMS-D-12-00014.1

Do probabilistic forecasts lead to better decisions?
journal, January 2013

  • Ramos, M. H.; van Andel, S. J.; Pappenberger, F.
  • Hydrology and Earth System Sciences, Vol. 17, Issue 6
  • DOI: 10.5194/hess-17-2219-2013

Joint price and volumetric risk in wind power trading: A copula approach
journal, February 2017


Uncertainty Forecasts Improve Decision Making Among Nonexperts
journal, September 2009

  • Nadav-Greenberg, Limor; Joslyn, Susan L.
  • Journal of Cognitive Engineering and Decision Making, Vol. 3, Issue 3
  • DOI: 10.1518/155534309X474460

Operational Ensemble Prediction at the National Meteorological Center: Practical Aspects
journal, September 1993


Stochastic representation of model uncertainties in the ECMWF ensemble prediction system
journal, October 1999

  • Buizza, R.; Milleer, M.; Palmer, T. N.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 125, Issue 560
  • DOI: 10.1002/qj.49712556006

Use and communication of probabilistic forecasts: Use and Communication of Probabilistic Forecasts
journal, February 2016

  • Raftery, Adrian E.
  • Statistical Analysis and Data Mining: The ASA Data Science Journal, Vol. 9, Issue 6
  • DOI: 10.1002/sam.11302

Forecasting wind power – Modeling periodic and non-linear effects under conditional heteroscedasticity
journal, September 2016


Extending logistic regression to provide full-probability-distribution MOS forecasts
journal, September 2009

  • Wilks, Daniel S.
  • Meteorological Applications, Vol. 16, Issue 3
  • DOI: 10.1002/met.134

The Effect of Probabilistic Information on Threshold Forecasts
journal, August 2007

  • Joslyn, Susan; Pak, Karla; Jones, David
  • Weather and Forecasting, Vol. 22, Issue 4
  • DOI: 10.1175/WAF1020.1

A kinetic energy backscatter algorithm for use in ensemble prediction systems
journal, October 2005

  • Shutts, Glenn
  • Quarterly Journal of the Royal Meteorological Society, Vol. 131, Issue 612
  • DOI: 10.1256/qj.04.106

Probabilistic wind power forecasts using local quantile regression
journal, January 2004

  • Bremnes, John Bjørnar
  • Wind Energy, Vol. 7, Issue 1
  • DOI: 10.1002/we.107

Ensemble Forecasting at NMC: The Generation of Perturbations
journal, December 1993


Comparison between Singular Vectors and Breeding Vectors as Initial Perturbations for the ECMWF Ensemble Prediction System
journal, November 2008

  • Magnusson, Linus; Leutbecher, Martin; Källén, Erland
  • Monthly Weather Review, Vol. 136, Issue 11
  • DOI: 10.1175/2008MWR2498.1

Gridded probabilistic weather forecasts with an analog ensemble: Gridded Probabilistic Forecasts with an Analog Ensemble
journal, October 2017

  • Sperati, Simone; Alessandrini, Stefano; Delle Monache, Luca
  • Quarterly Journal of the Royal Meteorological Society, Vol. 143, Issue 708
  • DOI: 10.1002/qj.3137

A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction Systems
journal, May 2005

  • Buizza, Roberto; Houtekamer, P. L.; Pellerin, Gerald
  • Monthly Weather Review, Vol. 133, Issue 5
  • DOI: 10.1175/MWR2905.1

Improving Renewable Energy Forecasting With a Grid of Numerical Weather Predictions
journal, October 2017

  • Andrade, Jose R.; Bessa, Ricardo J.
  • IEEE Transactions on Sustainable Energy, Vol. 8, Issue 4
  • DOI: 10.1109/TSTE.2017.2694340

The ECMWF Ensemble Prediction System: Methodology and validation
journal, January 1996

  • Molteni, F.; Buizza, R.; Palmer, Tn
  • Quarterly Journal of the Royal Meteorological Society, Vol. 122, Issue 529
  • DOI: 10.1256/smsqj.52904

Stochastic representation of model uncertainties in the ECMWF Ensemble Prediction System
journal, October 1999

  • Buizza, R.; Miller, M.; Palmer, Tn
  • Quarterly Journal of the Royal Meteorological Society, Vol. 125, Issue 560
  • DOI: 10.1256/smsqj.56005

Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation
journal, June 2020


State forecasting and operational planning for distribution network energy management systems
conference, July 2016


Methodologies to determine operating reserves due to increased wind power
conference, January 2013

  • Holttinen, Hannele; Milligan, Michael; Ela, Erik
  • 2013 IEEE Power & Energy Society General Meeting
  • DOI: 10.1109/pesmg.2013.6673067

Path Forecast Evaluation
journal, January 2008


Stochastic representation of model uncertainties in the ECMWF Ensemble Prediction System
text, January 1999


    Works referencing / citing this record:

    Promoting the use of probabilistic weather forecasts through a dialogue between scientists, developers and end‐users
    journal, February 2019

    • Fundel, Vanessa J.; Fleischhut, Nadine; Herzog, Stefan M.
    • Quarterly Journal of the Royal Meteorological Society, Vol. 145, Issue S1
    • DOI: 10.1002/qj.3482

    Simulating wind power forecast error distributions for spatially aggregated wind power plants
    journal, September 2019

    • Miettinen, Jari; Holttinen, Hannele; Hodge, Bri‐Mathias
    • Wind Energy, Vol. 23, Issue 1
    • DOI: 10.1002/we.2410

    Statistical post‐processing of turbulence‐resolving weather forecasts for offshore wind power forecasting
    journal, April 2020

    • Gilbert, Ciaran; Messner, Jakob W.; Pinson, Pierre
    • Wind Energy, Vol. 23, Issue 4
    • DOI: 10.1002/we.2456

    The future of forecasting for renewable energy
    journal, September 2019

    • Sweeney, Conor; Bessa, Ricardo J.; Browell, Jethro
    • WIREs Energy and Environment, Vol. 9, Issue 2
    • DOI: 10.1002/wene.365

    Powering the 21st century by wind energy—Options, facts, figures
    journal, September 2019

    • Rohrig, K.; Berkhout, V.; Callies, D.
    • Applied Physics Reviews, Vol. 6, Issue 3
    • DOI: 10.1063/1.5089877

    Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36
    journal, February 2019

    • Würth, Ines; Valldecabres, Laura; Simon, Elliot
    • Energies, Vol. 12, Issue 4
    • DOI: 10.3390/en12040712

    Improving Prediction Intervals Using Measured Solar Power with a Multi-Objective Approach
    journal, December 2019

    • Aler, Ricardo; Huertas-Tato, Javier; Valls, José M.
    • Energies, Vol. 12, Issue 24
    • DOI: 10.3390/en12244713