Trading wind generation from short-term Probabilistic forecasts of wind power

被引:398
|
作者
Pinson, Pierre [1 ]
Chevallier, Christophe [1 ]
Kariniotakis, George N. [1 ]
机构
[1] Tech Univ Denmark, Informat & Math Modeling Dept, Lyngby, Denmark
关键词
decision-making; energy markets; forecasting; uncertainty; wind energy;
D O I
10.1109/TPWRS.2007.901117
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Due to the fluctuating nature of the wind resource, a wind power producer participating in a liberalized electricity market is subject to penalties related to regulation costs. Accurate forecasts of wind generation are therefore paramount for reducing such penalties and thus maximizing revenue. Despite the fact that increasing accuracy in spot forecasts may reduce penalties, this paper shows that, if such forecasts are accompanied with information on their uncertainty, i.e., in the form of predictive distributions, then this can be the basis for defining advanced strategies for market participation. Such strategies permit to further increase revenues and thus enhance competitiveness of wind generation compared to other forms of dispatchable generation. This paper formulates a general methodology for deriving optimal bidding strategies based on probabilistic forecasts of wind generation, as well as on modeling of the sensitivity a wind power producer may have to regulation costs. The benefits resulting from the application of these strategies are clearly demonstrated on the test case of the participation of a multi-MW wind farm in the Dutch electricity market over a year.
引用
收藏
页码:1148 / 1156
页数:9
相关论文
共 50 条
  • [41] Potential of trading wind power as regulation services in the California short-term electricity market
    Zhang, Zhao-Sui
    Sun, Yuan-Zhang
    Cheng, Lin
    ENERGY POLICY, 2013, 59 : 885 - 897
  • [42] Short-term prediction of the power production from wind farms
    Landberg, L
    JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 1999, 80 (1-2) : 207 - 220
  • [43] Quantifying Short-term Wind Power Variability
    Boutsika, Th.
    Santoso, S.
    2011 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING, 2011,
  • [44] A valorization of the short-term forecasting of wind power
    Cornalino, E.
    Gutierrez, A.
    Cases, G.
    Draper, M.
    Chaer, R.
    2012 SIXTH IEEE/PES TRANSMISSION AND DISTRIBUTION: LATIN AMERICA CONFERENCE AND EXPOSITION (T&D-LA), 2012,
  • [45] Wind Power Short-Term Forecasting System
    Dica, C.
    Dica, Camelia-Ioana
    Vasiliu, Daniela
    Comanescu, Gh
    Ungureanu, Monica
    2009 IEEE BUCHAREST POWERTECH, VOLS 1-5, 2009, : 508 - +
  • [46] Probabilistic upscaling and aggregation of wind power forecasts
    Janosch Henze
    Malte Siefert
    Sascha Bremicker-Trübelhorn
    Nazgul Asanalieva
    Bernhard Sick
    Energy, Sustainability and Society, 10
  • [47] Short-Term Power Forecasting for Wind Power Generation under Extreme Weather Conditions
    Song, Yuexin
    Chen, Yizhi
    Tang, Chenghong
    Wang, Wei
    Xiao, Hao
    Pei, Wei
    Yang, Yanhong
    2023 IEEE/IAS INDUSTRIAL AND COMMERCIAL POWER SYSTEM ASIA, I&CPS ASIA, 2023, : 1905 - 1911
  • [48] Quantifying the Influences on Probabilistic Wind Power Forecasts
    Schreiber, Jens
    Sick, Bernhard
    2018 3RD INTERNATIONAL CONFERENCE ON POWER AND RENEWABLE ENERGY (ICPRE), 2018, 64
  • [49] Probabilistic upscaling and aggregation of wind power forecasts
    Henze, Janosch
    Siefert, Malte
    Bremicker-Truebelhorn, Sascha
    Asanalieva, Nazgul
    Sick, Bernhard
    ENERGY SUSTAINABILITY AND SOCIETY, 2020, 10 (01)
  • [50] A review of short-term wind power probabilistic forecasting and a taxonomy focused on input data
    Bazionis, Ioannis K.
    Karafotis, Panagiotis A.
    Georgilakis, Pavlos S.
    IET RENEWABLE POWER GENERATION, 2022, 16 (01) : 77 - 91