Power Allocation Optimization Strategy of Gravity Energy Storage Based on Load Forecasting

In view of the limited capacity of peak regulation and frequency modulation (PRFM for short) in power system, an optimization strategy of PRFM power distribution in gravity energy storage system (GESS for short) based on load forecasting is proposed in this paper. Firstly, a load forecasting model based on GAN network is established to accurately predict the load in the power system, so as to provide planning and dispatching reference for the GESS to participate in PRFM. On this basis, considering the benefits, costs and constraints of the GESS to participate in PRFM auxiliary services, the GESS economic model participating in PRFM power distribution is established, and the particle swarm optimization algorithm is used to optimize the solution and determine the optimal power distribution result of the GESS. Finally, the effectiveness of the proposed power allocation optimization strategy is verified by using the simulation platform.