Current methods and advances in forecasting of wind power generation

被引:828
|
作者
Foley, Aoife M. [1 ,2 ,3 ]
Leahy, Paul G. [2 ,3 ]
Marvuglia, Antonino [4 ]
McKeogh, Eamon J. [2 ,3 ]
机构
[1] Queens Univ Belfast, Sch Mech & Aerosp Engn, Belfast BT9 5AH, Antrim, North Ireland
[2] Natl Univ Ireland Univ Coll Cork, Sch Engn, Dept Civil & Environm Engn, Cork, Ireland
[3] Natl Univ Ireland Univ Coll Cork, Environm Res Inst, Cork, Ireland
[4] Natl Univ Ireland Univ Coll Cork, Cork Constraint Computat Ctr 4C, Cork, Ireland
关键词
Meteorology; Numerical weather prediction; Probabilistic forecasting; Wind integration wind power forecasting; SHORT-TERM PREDICTION; SPEED PREDICTION; ENERGY; INTEGRATION; ALGORITHMS; FRAMEWORK; TERRAIN; MODELS; OUTPUT;
D O I
10.1016/j.renene.2011.05.033
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:1 / 8
页数:8
相关论文
共 50 条
  • [1] Current status and future advances for wind speed and power forecasting
    Jung, Jaesung
    Broadwater, Robert P.
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2014, 31 : 762 - 777
  • [2] Current advances and approaches in wind speed and wind power forecasting for improved renewable energy integration: A review
    Santhosh, Madasthu
    Venkaiah, Chintham
    Kumar, D. M. Vinod
    [J]. ENGINEERING REPORTS, 2020, 2 (06)
  • [3] AN OVERVIEW ON WIND POWER FORECASTING METHODS
    Chai, Songjian
    Xu, Zhao
    Lai, Loi Lei
    Wong, Kit Po
    [J]. PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOL. 2, 2015, : 765 - 770
  • [4] A combined method for wind power generation forecasting
    Tuan-Ho Le
    [J]. ARCHIVES OF ELECTRICAL ENGINEERING, 2021, 70 (04) : 991 - 1009
  • [5] Forecasting of Solar and Wind Resources for Power Generation
    Islam, M. K.
    Hassan, N. M. S.
    Rasul, M. G.
    Emami, Kianoush
    Chowdhury, Ashfaque Ahmed
    [J]. ENERGIES, 2023, 16 (17)
  • [6] Review on probabilistic forecasting of wind power generation
    Zhang, Yao
    Wang, Jianxue
    Wang, Xifan
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2014, 32 : 255 - 270
  • [7] A Hybrid Model for Forecasting Wind Speed and Wind Power Generation
    Chang, G. W.
    Lu, H. J.
    Hsu, L. Y.
    Chen, Y. Y.
    [J]. 2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM), 2016,
  • [8] Methods and Prospects for Probabilistic Forecasting of Wind Power
    Wu W.
    Qiao Y.
    Lu Z.
    Wang N.
    Zhou Q.
    [J]. Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2017, 41 (18): : 167 - 175
  • [9] A Review on Different Methods of Wind Power Forecasting
    Agarwal, Parnika
    Shukla, Prakeern
    Sahay, Kishan Bhushan
    [J]. 2018 6TH INTERNATIONAL ELECTRICAL ENGINEERING CONGRESS (IEECON), 2018,
  • [10] WIND FARM CLUSTERING METHODS FOR POWER FORECASTING
    Goudarzi, Navid
    Ziaei, Dorsa
    [J]. PROCEEDINGS OF THE ASME 2022 POWER CONFERENCE, POWER2022, 2022,