Enhancing MPPT Control of Variable Wind Turbines: A Comparative Study of Optimal PI Controllers with the Novel GJO algorithm and the PSO and HHO algorithms

Our work focuses on the development of a control architecture for a wind turbine with variable wind based on the development and implementation of the MPPT (Maximum Power Point Tracking) control strategy. The main contribution lies in evaluating the effectiveness of integrating the novel GJO (Golden Jackal Optimization) algorithm alongside traditional meta-heuristic algorithms like PSO (Particle Swarm Optimization) and HHO (Harris Hawks Optimization) in optimizing the gain parameters of the speed controller. The goal is to optimize the power provided by the wind turbine with variable winds. A comparative analysis of these approaches assesses their efficacy in optimizing the mechanical speed of our system for maximum power output. Simulation results conducted in MATLAB/Simulink demonstrate that the proposed algorithms significantly enhance the efficiency and robustness of the MPPT control system. This study highlights the potential of the GJO algorithm to outperform traditional methods, representing a notable advancement in wind energy control strategies.