Abstract Wind turbine system due to its aerodynamic and generator components is a nonlinear and strongly coupled system. These characteristics influence the efficiency and performance of the systems output. In order to improve the efficiency of Maximum Power Point Tracking (MPPT) and to produce more green energy, a novel control strategy which is based on RBF neural network is designed. The proposed algorithm depends on the optimal tip speed ratio and adjusts rapidly the output of torque with the random wind. Finally, to validate and demonstrate the performance of the proposed method, the FAST and Matlab/Simulink are used to test under different conditions of Wind.
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A RBF Neural Network based MPPT Method for Variable Speed Wind Turbine System
Semantic Scholar · Engineering · 2015
Abstract
Abstract Wind turbine system due to its aerodynamic and generator components is a nonlinear and strongly coupled system. These characteristics influence the efficiency and performance of the systems output. In order to improve the efficiency of Maximum Power Point Tracking (MPPT) and to produce more green energy, a novel control strategy which is based on RBF neural network is designed. The proposed algorithm depends on the optimal tip speed ratio and adjusts rapidly the output of torque with the random wind. Finally, to validate and demonstrate the performance of the proposed method, the FAST and Matlab/Simulink are used to test under different conditions of Wind.
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