Optimization of maximum power point tracking in wind energy systems: a comparative study of ant colony and genetic algorithms

Najoua Mrabet, Chirine Benzazah, Mohssine Chakib, Adil Ziraoui, Ahmed El Akkary, Najma Laaroussi

Abstract


This research focuses on optimizing maximum power point tracking (MPPT) in wind energy conversion systems (WECS) using ant colony optimization (ACO) and genetic algorithm (GA). The study evaluates these two metaheuristic techniques to optimize the parameters of a proportional integral-derivative (PID) controller in order to maximize power output in a permanent magnet synchronous generator (PMSG)-based system. Simulations conducted in MATLAB/Simulink show that both ACO and GA effectively enhance MPPT performance by improving power output, DC bus voltage regulation, and torque stability. The results demonstrate the potential of metaheuristic algorithms to optimize wind energy conversion efficiency and support sustainable energy development.

Keywords


Ant colony; Genetic algorithm; Maximum power point tracking; Permanent magnet synchronous generator; PID controller

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DOI: http://doi.org/10.11591/ijai.v15.i1.pp399-411

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Copyright (c) 2026 Najoua Mrabet, Chirine Benzazah, Mohssine Chakib, Adil Ziraoui, Ahmed El Akkary, Najma Laaroussi

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES).

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