Review and Improvement of Several Optimal Intelligent Pitch Controllers and Estimator of WECS via Artificial Intelligent Approaches

摘要: Wind turbines in megawatt classification ordinarily rotate at variable speed wind farm. Therefore turbine operation must be managed order to maximize the conversion efficiency below rated power and reduce loading on drive-train. In addition, control energy captured throughout above speed, researchers particularly employ pitch of blades. Thus, we could manage using This chapter suggests six new plans conquer fluctuation problems based a Nero Fuzzy Genetic Controller where fuzzy knowledge are tuned automatically by Algorithm (GA) as known Tuned System (TFGS). Additionally this Chapter, hybrid has been trained that Energy Conversion (WECS) optimal performance. method contains Multi-Layer Perceptron (MLP) Neural Network (NN) (MLPNN) Rule extraction from Trained Artificial (FRENGA). Proposed Hybrid recognizes disturbance with sensors it generates desired angle comparison between FRENGA MLPNN results. One them better signal is selected send blade controller. Consequently strategies reject Systems (WECSs) input angel generation. Consequently, proposed approaches have regulated output aerodynamic torque nominal range. Results indicate Intelligent (AI) methods system outperform best earliest controlling during fluctuation.