MAXIMUM POWER POINT TRACKING CONTROL OF A WIND GENERATOR BASED ON PID CONTROLLER AND PARTICLE SWARM OPTIMIZATION ALGORITHM

Abstract

This paper proposes a maximum power point tracking control method for a doubly-fed induction generator in a wind power system to optimize power generation. A PID controller is used to regulate the rotor current, thereby adjusting the electromagnetic torque of the doubly-fed induction generator to achieve maximum power output. To enhance control performance, a particle swarm optimization algorithm is applied to automatically determine the optimal parameters K_p, K_i, and K_d of the PID controller. Simulation results demonstrate that the proposed method enables significantly improved maximum power point tracking compared to a conventional PID controller, especially under rapidly and continuously varying wind speeds. The average maximum power point tracking error using the particle swarm optimization algorithm-optimized PID controller and the conventional PID controller is 0.83% and 7.1%, respectively. This demonstrates the effectiveness of combining the PID controller with the particle swarm optimization algorithm in controlling the maximum power point tracking of the doubly-fed induction generator, contributing to improved wind energy harvesting efficiency, as well as enhancing the stability and reliability of the wind turbine power system.