A Collaborative Planning Method for Distributed Energy Storage Based on Differentiated Demands

With the continuous increase in the proportion of wind and solar power, the strong randomness and volatility of distributed new energy output have brought great challenges to the planning, regulation, and operation of the new distribution system. Distributed energy storage, with its characteristics such as scattered location distribution, flexible installation, small capacity, and diverse forms and application scenarios, is increasingly becoming an important resource and technical means to enhance the consumption capacity of new energy and ensure the safe and reliable operation of the power system. This paper proposes a collaborative planning method for distributed energy storage based on differentiated demands. First, the typical application scenarios of distributed energy storage are analyzed; secondly, the source–load matching degree and modularity are proposed as cluster division indicators. Voltage fluctuation, load fluctuation, and the net income of distributed energy storage are combined into multiple optimization objectives. Based on differentiated demands, a two-layer optimal configuration model of distributed energy storage is proposed and solved by using the improved particle swarm optimization algorithm. Finally, the feasibility and effectiveness of the proposed method were verified through a modified IEEE33 node simulation example.