Research of ASW-FCM-Based Algorithm for Clustered Wind Turbine Group Equivalent Modeling

Abstract

A new dynamic equivalent modeling method for a wind farm composed of direct-drive wind turbines is proposed. Firstly, the effective input wind speed is calculated considering the wake effect and wind direction change between wind turbines, the operating characteristics is analyzed, the effective wind speed, rotor speed, pitch angle and output power that reflect the wind turbine operating characteristics are selected as the multi-grouping indicators. Secondly, an adaptive sample weighting fuzzy C-means clustering algorithm (ASW-FCM) considering the differences and correlations among turbines operating conditions is designed to cluster the wind farm optimally. Then the equivalent model of the clustered wind turbine group is established based on the principle that the output characteristics before and after the equivalence are equal. Finally, an actual wind farm system is used as an example for modeling and simulation to verify the rationality and accuracy of the equivalent modeling method.