Research on the revenue prospect for energy storage participation in electricity spot and FM auxiliary service markets —Considering capacity market mechanisms

Abstract

Abstract The vigorous development of energy storage is significant in supporting new energy consumption and enhancing the power system regulation capability. The spot and auxiliary service markets are the core ways for energy storage to realize commercial value. This paper establishes a revenue prediction model for energy storage participation in the electricity spot and FM auxiliary service market from the perspective of the revenue outlook of energy storage investment, including electric energy spot revenue, spot response incentive revenue considering capacity market price, and FM capacity revenue and FM mileage revenue. Specifically, the BP neural network prediction model, the FM clearing prediction model, and the capacity market supply and demand model are used to combine a variety of influencing factors to predict the spot price spread of electric energy, the FM mileage price, and the capacity price, which are then solved by substituting other parameters into the model. The results show that the method proposed in this paper is favorable for energy storage investment cost recovery and has good economics.