INTELLIGENT MPPT CONTROL FOR WIND ENERGY CONVERSION SYSTEMS BASED REINFORCEMENT LEARNING

Abstract

This paper proposes a reinforcement learning (RL) method based maximum power point tracking (MPPT) algorithm for wind energy conversion systems (WECS).Due to the non-linear properties of the wind generator, the architecture takes the MPPT approach to track the effective power generated from the wind systems.This article presents the design in MATLAB/Simulink for WECS.Since RL helps the WECS to improve by direct interaction with the atmosphere, it requires no information of wind turbine specifications or wind velocity information.The key part of this role is the DC-DC model that is built in very detail, which enables the performance of the MPPT controller to change the voltage input of the converter to control the highest wind power system point.