A new hybrid optimal control for WECS using MLP Neural Network and Genetic neuro Fuzzy

New wind turbines usually is working in variable speed and variable pitch angle. Thus, we could manage the energy captured throughout operation above and below rated wind speed using pitch control of the blades. In this study, a new hybrid control has been proposed. This method contains a Multi-Layer Perceptron (MLP) Neural Network (NN) (MLPNN) and a Fuzzy Rule extraction from a Trained Artificial Neural Network using Genetic Algorithm (FRENGA). Our proposed Hybrid method recognizes disturbance wind with sensors and it generates desired pitch angle control by comparison between FRENGA and MLPNN results. One of them has better signal control is selected. Consequently, output power has been regulated in the nominal range. Results indicate that the new proposed method outperforms other nearest methods in controlling the output during wind fluctuation.