Evaluation of the MPPT for the Wind Energy Conversion System's Performance using ANN and ANFIS

Abstract

For wind system maximum power point tracking, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), have been described. Both the ANN and ANFIS-based controllers can track the maximum power (MP) and by estimating wind speed with a small margin of error. The back-propagation method is used to train the network during the learning phase, and the gradient-decent search strategy is employed to alter the weights between nodes to reduce error. The ANFIS network, on the other hand, combines the artificial neural network and the fuzzy decision process to produce a more efficient decision process. To determine wind speed, neither technique requires a mechanical sensor. According to the simulation results, the ANN and ANFIS algorithms are suitable for determining wind velocity and tracking the highest power point and corresponding rotor speed. In terms of wind velocity estimation, the ANFIS-based controller is more exact and robust than the ANN -based MPPT Controller. The suggested controller is implemented in MATLAB/ Simulink for analysis and testing.