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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Larbi Chrifi-Alaoui
Picardie Jules Verne University

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Metaheuristic optimization of wind turbine farm siting in power grids: a comparative study of PSO and GA Taha Rachdi; Yahia Saoudi; Larbi Chrifi-Alaoui; Ayachi Errachdi
Indonesian Journal of Electrical Engineering and Computer Science Vol 42, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v42.i3.pp666-677

Abstract

This paper addresses the optimal integration of wind turbines into distribution networks with the aim of reducing active power losses and improving voltage stability. Two metaheuristic optimization methods genetic algorithm (GA) and particle swarm optimization (PSO) are applied to determine the optimal siting and sizing of wind turbines in the IEEE 14-bus system. The problem is formulated as a multi-objective function combining loss minimization and voltage profile enhancement under standard network constraints. Simulation results using MATLAB/PSAT show that both algorithms improve system performance compared to the base case, with PSO providing superior loss reduction and voltage stability. Wind variability is represented through a Weibull distribution to reflect realistic operating conditions. The study demonstrates the effectiveness of metaheuristic optimization for renewable integration and highlights PSO’s stronger robustness. The work contributes a comparative evaluation of GA and PSO, supported by stability analysis and realistic wind modelling.
Co-Authors Ayachi Errachdi Taha Rachdi Yahia Saoudi