Dynamic equivalent modeling of two-staged photovoltaic power station clusters based on dynamic affinity propagation clustering algorithm

This paper presents a novel dynamic clustering equivalent modeling method for a two-staged photovoltaic (PV) station cluster, which is a key tool to analyze the dynamic responses of the distribution network with high PV penetration. In this paper, a dynamic affinity propagation (DAP) clustering algorithm is proposed after studying the indexes that can describe the dynamic characteristics of two-staged PV power station. Then this algorithm is used to group the PV stations in the PV cluster according to their dynamic characteristics. Finally, the dynamic equivalent model of PV cluster is obtained by parameters aggregation of PV stations in the same group and simplification equivalent of the network. The proposed method is verified by a PV cluster distribution network with 20 two-staged PV stations and the simulation results show that the proposed dynamic equivalent model can accurately reflect the dynamic response characteristics of the PV cluster. At the same time, the simplified PV cluster model would reduce the computational complexity and the simulation time significantly.