Primary Frequency Control Strategy of DFIG Based on Hopfield Neural Network

Abstract

This paper presents a new method to enhance the participation of doubly fed induction generators (DFIG) effectively in system frequency regulation. A new associated control based on Hopfield neural network (HNN) is proposed to control the rotor kinetic energy and the primary reserve power of DFIG simultaneously. The proposed approach takes advantage of the learning ability of neural network to form an adaptable Hopfield neural network controller (HNNC). And the feasibility of all those control strategies is analyzed in a Two-area four-generator system based on PSCAD/EMTDC. Simulation results indicate that the proposed strategy can greatly improve system frequency stability compared with classical strategies.