Study on the optimization of the day-ahead addition space for large-scale energy storage participation in auxiliary services

Energy storage signs bilateral trading plans with new energy power plants according to the monthly forecast of new energy output, and reports adjustable space to the dispatch before the day. As for the large error in the monthly forecast of new energy output, energy storage can make a day-ahead forecast and report additional space according to the difference between it and the monthly forecast, i.e. report additional space, to improve the economic efficiency of energy storage power plants. We obtain the new energy next day output prediction results based on the scenario generation method. In order to maximize the net revenue of daily operation of energy storage, an optimization model of the storage day-ahead add-on space is established based on the comprehensive consideration of auxiliary service revenue, battery aging cost and penalty risk. The simulation of the proposed strategy based on the model shows that the optimization results obtained in this paper can make fuller use of large-scale energy storage resources and improve the economic efficiency of energy storage plants.