Artificial Neural Network Control Strategy for Wind Energy Conversion System

Abstract

Wind energy is one of the most effective types of clean renewable energies contributing to energy security and sustainable development at the same time. In this paper, artificial intelligence is integrated into the wind energy conversion system (WECS) control units, where an artificial neural network, referred to as (ANN), is designed to control the electromagnetic torque through the stator currents of the permanent magnet synchronous generator (PMSG), ensuring the maximum power point tracking (MPPT). Thus, driving the system to produce as much electricity as possible from the available wind power. By simulating the overall system in MATLAB/ Simulink software, the results show the efficiency and good performance of the proposed control strategy under a variable wind model.