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Abstract Numerous areas of power systems require finding solutions to nonlinear optimization issues, such as, the optimal location of wind turbines. In order to enhance the voltage profile and reduce line power losses. This research suggests two optimization techniques for figuring out the best wind turbine location in a distribution system. The suggested methodology based on particle swarm optimization (PSO) and genetic algorithm (GA) techniques to minimize the objective function. These algorithms are applied for IEEE 14 bus distribution system using MATLAB R2010a and the Power System Analysis Toolbox (PSAT). The results indicate that the obtained optimal values of the wind turbine location using particle swarm optimization technique are located at bus numbers 3, 6, 7, and 9, with a reduction in power losses of 85%. Additionally, the voltage profile across the system buses showed significant improvement, maintaining the voltage levels within permissible limits and closer to the nominal values. The genetic algorithm also provided effective results, demonstrating the robustness of both methods in addressing the optimization problem. Overall, this study highlights the potential of GA and PSO in enhancing the efficiency and reliability of power distribution systems by strategically integrating wind turbines. The comparative analysis between the two algorithms provides valuable insights into their performance, convergence characteristics, and computational efficiency, making them viable tools for modern power system optimization
Rachdi et al. (Wed,) studied this question.