Dynamic clustering equivalent model of wind turbines based on spanning tree

Abstract

With the increasingly high penetration of wind energy, the dynamic influence of wind farms (WFs) on operation security of power systems gains much more attention. Consisting of hundreds of wind turbines (WTs), dynamic analysis on a detailed model of WFs is complicated and time consuming. In this paper, a simplified dynamic equivalent model of WFs based on the spanning tree (ST) is proposed. First, the clustering method based on the growing ST is first applied to the dynamic equivalent of WFs. Second, according to the mathematical model of doubly fed induction generator (DFIG) and permanent magnetic synchronous generator (PMSG), clustering variables of DFIG and PMSG are classified into internal variables and external variables, reflecting the dynamic characteristics of WTs. Finally, based on the actual WFs and actual wind speed data, simulations were employed in DIGSILENT/PowerFactory. The results demonstrate that the proposed model is able to precisely reflect the dynamic characteristics of WFs in both fault condition and fluctuation of wind speed. With time reducing, the effectiveness and feasibility of the proposed model has been verified.