PROJECT TITLE :

A Fuzzy Clustering Algorithm-Based Dynamic Equivalent Modeling Method for Wind Farm With DFIG

ABSTRACT:

With the increasing capability of grid connected wind farms, the influence of wind power to stable operation of an electrical power system is becoming additional and a lot of necessary. In order to investigate the active power output characteristics of wind farm, a multimachine illustration dynamic equivalent technique based on the fuzzy clustering algorithm is proposed. 1st, indicators which can characterize the active power output performance of a doubly fed induction wind generator (DFIG) are researched. Second, a fuzzy C-means that (FCM) clustering algorithm is initial applied to the modeling of wind farm. DFIGs are divided into teams by analyzing the indicator knowledge with FCM. Finally, DFIGs of the same group are equivalent collectively DFIG to realize the dynamic equivalent modeling of wind farm with DFIG. Simulation results demonstrated that the established dynamic equivalent model can replicate the active power dynamic response characteristics of wind farm with DFIG effectively; meanwhile, the model of wind farm is simplified and computation complexity is reduced.