Combined use of Sensitivity Analysis and Hybrid Wavelet-PSO- ANFIS to Improve Dynamic Performance of DFIG-Based Wind Generation

In the past few decades, increasing growth of wind power plants causes different problems for the power quality in thegrid. normal and transient impacts of these units on the power grid clearly indicate the need to improve the quality ofthe electricity generated by them in the design of such systems. improving the efficiency of the large-scale wind systemis dependent on the control parameters. the main contribution of this study is to propose a sensitivity analysisapproach integrated with a novel hybrid approach combining wavelet transform, particle swarm optimization and anadaptive-network-based fuzzy inference system (anfis) known as wavelet-anfis-pso to acquire the optimalcontrol of doubly-fed induction generators (dfig) based wind generation. in order to mitigate the optimizationcomplexity, sensitivity analysis is offered to identify the unified dominate control parameters (udcp) rather thanoptimization of all parameters. the robustness of the proposed approach in finding optimal parameters, andconsequently achieve a high dynamic performance is confirmed on two area power system under different operatingconditions.