Distributed Energy Storage with Peak Shaving and Voltage Regulation Considerations

Traditional clustering methods based on a single criterion have become insufficient to meet the planning and operational requirements of modern distribution networks. This paper addresses this challenge by introducing a novel clustering method that integrates both structural and functional considerations. The proposed method is applied to distribution network planning scenarios involving distributed generation and heterogeneous distributed energy storage systems. Furthermore, we present distinct clustering strategies for distributed energy storage systems tailored to their roles in peak shaving and voltage regulation tasks. Specifically, we propose a cluster control strategy for distributed energy storage in peak shaving and valley filling. These strategies are designed to optimize the performance and economic efficiency of multi-type distributed energy storage clusters in peak shaving and voltage regulation applications.