Research on Planning and Dispatching Strategy of Grid-Side Energy Storage Power Station Considering Regional Power Grid Interconnection

Energy storage planning and optimal dispatch in real power grids are restricted by high-dimensional nonlinear constraints. The solution process involves a heavy calculation burden. This paper studies the site selection, capacity sizing and optimal dispatch of large-scale grid-side energy storage stations for 220 kV regional power grids. First, a multi-objective optimization model is constructed. It takes two indicators as sub-objectives: total installed capacity of energy storage stations and net load peak–valley difference. Then, a customized improved particle swarm optimization (IPSO) algorithm is designed. This algorithm is improved from the classic gray relationship analysis–particle swarm optimization (GRA–PSO). It targets the site and allocation of electrochemical battery energy storage stations (BESSs) inside interconnected 220 kV regional grids. Unlike the GRA–PSO structure presented in existing studies, this paper reconstructs the gray correlation sequence matching the multi-objective planning demand of regional power grids and introduces differentiated particle velocity constraints based on node load characteristics. By combining gray correlation with PSO, premature convergence and clustered storage layout introduced by traditional PSO can be eliminated. Subsequently, taking the renewable energy accommodation rate and net load peak–valley difference rate as optimization objectives, this paper adopts the walrus optimization algorithm (WOA) to carry out optimal dispatching of BESSs in regional power grids. A fitness-variance early-stop rule is introduced to the WOA for ESS dispatching, cutting redundant iterations while balancing peak-shaving and renewable energy curtailment reduction. Finally, numerical analysis of a case study based on a typical urban 220 kV regional power grid in central Henan Province, China, verifies the effectiveness and reliability of the proposed strategy.