Current methods and advances in forecasting of wind power generation

Aoife M. Foley, P.G. Leahy, Antonino Marvuglia, E.J. McKeogh

Research output: Contribution to journalReview articlepeer-review

716 Citations (Scopus)
280 Downloads (Pure)

Abstract

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised. (C) 2011 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)1-8
JournalRenewable Energy
Volume37
Issue number1
Early online date01 Jul 2011
DOIs
Publication statusPublished - Jan 2012

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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