Neural network theory based voltage and frequency controller for standalone wind energy conversion system

Abstract

In this paper, a solid state voltage and frequency (VF) controller is proposed for a standalone wind energy conversion system (WECS) employing a permanent magnet synchronous generator (PMSG). The proposed VF controller consists of IGBTs (insulated gate bipolar transistors) based three-leg voltage source converter (VSC) with a battery energy storage system (BESS) at its dc link. The Adaline (adaptive linear element) based neural network is used to control the VSC of the proposed VF controller. The Adaline control technique is simple and has a fast response. The VF controller is controlled to inject and absorb both active power and reactive power so that both frequency and the system voltage are regulated under varying consumer loads and wind speeds. The VF controller also functions as a harmonic compensator and a load balancer. The performance of the proposed VF controller is simulated using MATLAB software with its Simulink and SimPower System (SPS) toolboxes.