A Dynamic Weighted Aggregation Equivalent Modeling Approach for the DFIG Wind Farm Considering the Weibull Distribution for Fault Analysis

Abstract

The developing process of the aggregated dynamic equivalent model (DEM) for doubly-fed induction generator (DFIG) wind farms could be less computational and more efficient compared with the multimachine DEM, but less accurate when wind speed differences exist inside the wind farm. In addition, the wind speed differences contribute to the different activation patterns of the crowbar systems of DFIGs. Therefore, a dynamic weighted aggregation modeling approach is proposed in this paper to improve the applicability of the aggregated DEM for DFIG wind farm. First, the Gaussian density distance clustering algorithm is applied to segment the wind speed power curve into different zones such that each segmented zone is corresponded to one equivalent aggregated machine. Then the dynamic weighted aggregation equivalent model could be developed based on the conventional aggregated DEM, where the weighting factors for each generator are calculated according to the Weibull distribution of wind speeds. Different scenarios are simulated in MATLAB/Simulink environment to analyze the applicability of the proposed dynamic weighting equivalent model. The simulation results show the effectiveness of the proposed method.