Genetic Algorithm-based MPPT For Wind Power Conversion System: Study And Comparison With Conventional Method In Tropical Climate

Abstract

This paper presents a genetic algorithm-based maximum power point tracking (MPPT) technique for wind power systems. The proposed method aims to overcome the drawbacks of the well-known perturb and observe (P& O) algorithms, such as oscillation around the maximum power point (MPP) and overall system stability. Given the non-linear mathematical model of wind turbines, intelligent search algorithms (ISAs), such as genetic algorithms, are well-suited for MPPT applications. The proposed method is designed to be computationally efficient and has a simple structure for ease of implementation. Simulation results, obtained using the MATLAB/SIMULINK environment, are compared between the proposed genetic algorithm-based MPPT and the traditional P& O technique under a typical day of data measured on the Morne à Cabrit site (Region east of Port-au-Prince, Haiti). The results demonstrate that the proposed technique rapidly tracks the MPP while significantly reducing steady-state oscillation.