1. Improving offering strategies for wind farms enhanced with storage capability
- Author
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Yonghua Song, Pierre Pinson, Huajie Ding, and Zechun Hu
- Subjects
Mathematical optimization ,Artificial intelligence ,wind power deviation ,Power, Energy and Industry Applications ,Computer science ,energy storage system ,wind farm ,wind power plants ,Profit (economics) ,Energy storage ,storage capability ,two-price balancing market rules ,wind power forecast error ,real-time operation ,electricity markets ,ESS ,day-ahead bidding strategy ,Simulation ,Wind power ,Balancing market ,business.industry ,energy storage ,wind farms ,Bidding ,Bidding strategy ,power markets ,Electricity ,Arbitrage ,day-ahead contracts ,business ,Gradient descent ,operation strategy ,gradient methods ,gradient descent algorithm - Abstract
Due to the flexible charging and discharging capability, energy storage system (ESS) is thought of as a promising complement to wind farms (WF) in participating into electricity markets. This paper proposes a reserve-based real-time operation strategy of ESS to make arbitrage and to alleviate the wind power deviation from day-ahead contracts. Taking into account the operation strategy as well as two-price balancing market rules, a day-ahead bidding strategy of WF-ESS system is put forward and formulated. A modified gradient descent algorithm is described to solve the formulations. In the case studies, the computational efficiency of the algorithm is validated firstly. Moreover, a number of scenarios with/without considering the temporal dependence of wind power forecast error are designed and employed to compare the proposed strategy with other common ones in terms of profit.
- Published
- 2015