Equivalent Modeling of PV Cluster Dynamic Process Based on K-medoids Clustering

Aiming at the problems of high complexity and long simulation time of existing dynamic process model of photovoltaic (PV) cluster, an equivalent modeling method of dynamic process of PV cluster based on K-medoids clustering algorithm is proposed in this paper. Firstly, the parameters that reflect the dynamic characteristics of PV power stations in real time are selected as clustering features. The dynamic similarity between PV power stations is represented by the dynamic time warping (DTW) distance. Secondly, the PV power stations are clustered based on K-medoids clustering algorithm. Finally, based on the clustering results, the parameters of PV power stations are equivalently processed, and the corresponding PV cluster dynamic surrogate model is established. The rigorous model and equivalent model of PV cluster dynamic process are built by Simulink platform. Two fault conditions, the load mutation and point of common coupling (PCC) voltage sag, are simulated. The experimental results based on IEEE-33 bus system verify that the dynamic surrogate model based on K-medoids clustering has good dynamic simulation accuracy. At the same time, the simulation time and model complexity are significantly reduced compared with the rigorous model.