Sensorless MPPT Controller using Particle Swarm and Grey Wolf Optimization for Wind Turbines

This paper proposes a sensorless MPPT controller using Particle Swarm and Grey Wolf Optimization for wind turbines. MPPT controllers are used to track the maximum power point regardless of wind speed. Earlier proposed methods like P&O, Fuzzy Logic, Artificial Neural Networks suffers from steady state and lower efficiency. In addition to the power subjected to maximization, the proposed algorithms, Particle Swarm and Grey Wolf, do not need any additional wind sensor or prior knowledge of the wind energy system. Those proposed evolutionary computation techniques assure zero steady state oscillation and faster convergence while tracking maximum power. In this work, the MATLAB/Simulink environment is used to simulate the proposed PSO & GWO algorithms. The obtained results demonstrate that the adopted techniques are significantly more efficient than traditional algorithms.