Insurance strategy for mitigating power system operational risk introduced by wind power forecasting uncertainty. (April 2016)

• Record Type: Journal Article
• Authors: Yang, Hongming; Qiu, Jing; Meng, Ke; Zhao, Jun Hua; Dong, Zhao Yang; Lai, Mingyong
• Is Part Of: Renewable energy. Volume 89(2016)
• Page Start: 606
• Page End: 615
• Publication Date: 2016-04
• Subjects: Electricity market -- Insurance strategy -- Risk sharing -- Underwriting premiums -- Wind power forecast errors; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2015.12.007
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: 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. Highlights: A hybrid ESS and insurance strategy is proposed to mitigate power imbalance risks. Monte Carlo simulations are undertaken to estimate insurance premiums. Effects of different insurance excesses and wind farm capacities are compared. Results reveal that the proposed strategy is a promising risk aversion approach.