MPPT control of wind turbines by direct adaptive fuzzy-PI controller and using ANN-PSO wind speed estimator

Abstract

This paper proposes a maximum power point tracking (MPPT) technique based on the tip speed ratio control for small scale wind turbines (WTs). In this paper, artificial neural network based particle swarm optimization has been trained offline to learn the characteristic of the turbine power as a function of wind and machine speeds. Afterwards, it has been realized online to estimate the varying wind speed. It is essential to design a controller that can track the maximum peak of energy regardless of wind speed changes. Therefore, this work provides a novel robust direct adaptive fuzzy–Proportional-Integral (PI) controller during the MPPT process through tuning duty cycle of the boost converter for permanent magnet synchronous generator driven by a WT. The proposed method has successfully decreased the ripples of coefficient of power (Cp) which is the index of MPPT mode, under variations of the wind speed in comparison with conventional controller. Finally, a systematic analysis is presented which is in good agreement with simulation results, confirming the effectiveness of the proposed strategy.<br><br>I. INTRODUCTION