Insurance strategy for mitigating power system operational risk introduced by wind power forecasting uncertainty

被引:17
|
作者
Yang, Hongming [1 ]
Qiu, Jing [2 ]
Meng, Ke [2 ]
Zhao, Jun Hua [5 ]
Dong, Zhao Yang [3 ]
Lai, Mingyong [4 ]
机构
[1] Changsha Univ Sci & Technol, Hunan Prov Key Lab Smart Grids Operat & Control, Elect Transportat & Smart Distributed Network, Hunan Prov Engn Res Ctr,Sch Elect Engn & Informat, Changsha 410114, Hunan, Peoples R China
[2] Univ Newcastle, Ctr Intelligent Elect Networks, Callghan, NSW 2308, Australia
[3] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW 2006, Australia
[4] Changsha Univ Sci & Technol, Sch Econ & Management, Changsha 410114, Hunan, Peoples R China
[5] Chinese Univ Hong Kong Shenzhen, Shenzhen, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Electricity market; Insurance strategy; Risk sharing; Underwriting premiums; Wind power forecast errors; GENERATION; ERRORS; COSTS;
D O I
10.1016/j.renene.2015.12.007
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The increasing penetration of wind power significantly affects the reliability of power systems due to its intrinsic intermittency. Wind generators participating in electricity markets will encounter operational risk (i.e. imbalance cost) under current trading mechanism. The imbalance cost arises from the service for mitigating supply-demand imbalance caused by inaccurate wind forecasts. In this paper, an insurance strategy is proposed to cover the possible imbalance cost that wind power producers may incur. First of all, a novel method based on Monte Carlo simulations is proposed to estimate insurance premiums. The impacts of insurance excesses on premiums are analyzed as well. Energy storage system (ESS) is then discussed as an alternative approach to balancing small wind power forecasting errors, whose loss claims would be blocked by insurance excesses. Finally, the ESS and insurance policy are combined together to mitigate the imbalance risks of trading wind power in real-time markets. With the proposed approach, the most economic power capacity of ESS can be determined under different excess scenarios. Case studies prove that the proposed ESS plus insurance strategy is a promising risk aversion approach for trading wind power in real-time electricity markets. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:606 / 615
页数:10
相关论文
共 50 条
  • [1] Development and Operational Status of Wind Power Forecasting System
    Aoki, Isao
    Tanikawa, Ryoichi
    Hayasaki, Nobuyuki
    Matsumoto, Mitsuhiro
    Enomoto, Shigero
    [J]. ELECTRICAL ENGINEERING IN JAPAN, 2014, 189 (04) : 22 - 29
  • [2] Wind speed forecasting for power system operational planning
    Wang, X
    Sideratos, G
    Hatziargyriou, N
    Tsoukalas, LH
    [J]. 2004 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS, 2004, : 470 - 474
  • [3] Power allocation strategy of wind power cluster considering power forecasting deviation and output regulation uncertainty
    Liu, Yu
    Zhao, Yanshun
    Zhang, Pei
    [J]. Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2024, 44 (02): : 110 - 116
  • [4] Evaluating operational risk in a power system with a large amount of wind power
    Gouveia, Eduardo M.
    Matos, Manuel A.
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2009, 79 (05) : 734 - 739
  • [5] Insurance Contracts for Hedging Wind Power Uncertainty
    D'Amico, Guglielmo
    Gismondi, Fulvio
    Petroni, Filippo
    [J]. MATHEMATICS, 2020, 8 (08)
  • [6] Wind power forecasting uncertainty and unit commitment
    Wang, J.
    Botterud, A.
    Bessa, R.
    Keko, H.
    Carvalho, L.
    Issicaba, D.
    Sumaili, J.
    Miranda, V.
    [J]. APPLIED ENERGY, 2011, 88 (11) : 4014 - 4023
  • [7] Reviews on uncertainty analysis of wind power forecasting
    Yan, Jie
    Liu, Yongqian
    Han, Shuang
    Wang, Yimei
    Feng, Shuanglei
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2015, 52 : 1322 - 1330
  • [8] Economic comparison of wind power curtailment and ess operation for mitigating wind power forecasting error
    [J]. Lee, Jaehee (jaehee@mokpo.ac.kr), 2018, Korean Institute of Electrical Engineers (67):
  • [9] Robust Wind Power Ramp Control Strategy Considering Wind Power Uncertainty
    Ren, Bixing
    Jia, Yongyong
    Li, Qiang
    Wang, Dajiang
    Tang, Weijia
    Zhang, Sen
    Astolfi, Davide
    [J]. ELECTRONICS, 2024, 13 (01)
  • [10] A WIND POWER FORECASTING SYSTEM TO OPTIMIZE POWER INTEGRATION
    Haupt, Sue Ellen
    Liu, Yubao
    Wiener, Gerry
    Myers, Bill
    Sun, Juanzhen
    Johnson, David
    Mahoney, William
    [J]. PROCEEDINGS OF THE ASME 5TH INTERNATIONAL CONFERENCE ON ENERGY SUSTAINABILITY 2011, PTS A-C, 2012, : 2213 - 2220