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
  • [31] Short-term Prediction Models for Wind Speed and Wind Power
    Bai, Guangxing
    Ding, Yanwu
    Yildirim, Mehmet Bayram
    Ding, Yan-Hong
    2014 2ND INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI), 2014, : 180 - 185
  • [32] Short-term Wind Power Probabilistic Prediction Considering Data and Model Uncertainties
    Yu J.
    Pang C.
    Dianwang Jishu/Power System Technology, 2022, 46 (05): : 1926 - 1933
  • [33] PROBABILISTIC MODELING OF SHORT-TERM WIND POWER PREDICTION ERRORS AND OUTPUT FLUCTUATIONS
    Ma W.
    Xie L.
    Ma L.
    Ye J.
    Bian Y.
    Yang Y.
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2023, 44 (11): : 361 - 366
  • [34] Open Source Tool for Probabilistic Short-Term PV and Wind Power Forecasting
    Mitrentsis, Georgios
    Liu, MengLing
    Lens, Hendrik
    2022 17TH INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS), 2022,
  • [35] An Efficient Scenario Generation Technique for Short-Term Wind Power Production
    Al-Awami, Ali T.
    Khalid, M. Waqas
    El-Sharkawi, M. A.
    2018 IEEE INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS), 2018,
  • [36] Time-consistent calibration of short-term regional wind power ensemble forecasts
    Spaeth, Stephan
    von Bremen, Lueder
    Junk, Constantin
    Heinemann, Detlev
    METEOROLOGISCHE ZEITSCHRIFT, 2015, 24 (04) : 381 - 392
  • [37] Probabilistic Forecasts of Wind Power Generation Accounting for Geographically Dispersed Information
    Tastu, Julija
    Pinson, Pierre
    Trombe, Pierre-Julien
    Madsen, Henrik
    IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (01) : 480 - 489
  • [38] Probabilistic Forecasts of Wind Power Generation by Stochastic Differential Equation Models
    Moller, Jan Kloppenborg
    Zugno, Marco
    Madsen, Henrik
    JOURNAL OF FORECASTING, 2016, 35 (03) : 189 - 205
  • [39] On the quality and value of probabilistic forecasts of wind generation
    Pinson, P.
    Juban, J.
    Kariniotakis, G. N.
    2006 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS, VOLS 1 AND 2, 2006, : 647 - 653
  • [40] Trading wind power through physically settled options and short-term electricity markets
    Papakonstantinou, Athanasios
    Champeri, Georgia
    Delikaraoglou, Stefanos
    Pinson, Pierre
    WIND ENERGY, 2019, 22 (11) : 1487 - 1499