دانلود مقاله ISI انگلیسی شماره 56885
ترجمه فارسی عنوان مقاله

استراتژی برای کاهش ریسک عملیاتی سیستم قدرت ارائه شده توسط عدم قطعیت پیش بینی قدرت بادی

عنوان انگلیسی
Insurance strategy for mitigating power system operational risk introduced by wind power forecasting uncertainty
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
56885 2016 10 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Renewable Energy, Volume 89, April 2016, Pages 606–615

ترجمه کلمات کلیدی
بازار برق؛ استراتژی ؛ اشتراک خطر؛ تعهد حق بیمه؛ خطاهای پیش بینی قدرت بادی
کلمات کلیدی انگلیسی
Electricity market; Insurance strategy; Risk sharing; Underwriting premiums; Wind power forecast errors
پیش نمایش مقاله
پیش نمایش مقاله  استراتژی برای کاهش ریسک عملیاتی سیستم قدرت ارائه شده توسط عدم قطعیت پیش بینی قدرت بادی

چکیده انگلیسی

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.