Abstract

In high renewable energy sources penetrated power systems, a large number of distributed small-capacity energy storages (ESs) are expected to form virtual power plants (VPPs) and provide comparable frequency regulation capacity to conventional power plants. In this paper, a dynamic and distributed partition method is proposed to cluster ESs into VPPs by selecting the electrical distance and local power demands as the index for partitioning. Utilizing the partition indices, the Personalized PageRank (PPR) scores are used to measure the similarity of all ESs with respect to other ESs in parallel. Then Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is utilized to partition the ESs into different VPPs. Within the VPPs, the secondary frequency control strategy is adopted to achieve the frequency regulation and state of charge (SoC) balancing. Finally, the performance comparison of the proposed partition method with several classic clustering algorithms is conducted to validate the efficiency and the quality of the partition. And numerical studies are performed in an IEEE 39-bus system to verify that the proposed control method can eliminate the frequency deviation and reduce power losses.

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