Cluster-Based Optimal Scheduling for Heterogeneous Energy Storage Stations

The integration of energy storage stations can provide flexibility for the power system. However, the massive distributed storage stations with different locations and characters pose the difficulties for optimal scheduling. This paper proposes a cluster-based optimal scheduling method for energy storage stations. The characteristics of storage nodes are effectively extracted using indicators electrical distance, energy efficiency coefficient, and response coefficient. The Louvain algorithm is applied to group spatially adjacent and technologically similar storage units into clusters. These aggregated clusters are then modeled as virtual storage units and integrated into a scheduling framework alongside thermal generators and renewable energy sources. Simulation results demonstrate that the proposed method enhances coordinated system control, significantly reduces computation time with only a minimal increase in total operating cost, and improves overall scheduling efficiency.