Enhanced Distributed Generation Placement Using Carpet Weaver Optimization: A Comparative Metaheuristic Approach

The optimal placement of Distributed Generation (DG) units is a key challenge in power distribution networks, directly affecting power losses, voltage stability, and system reliability.This study evaluates the effectiveness of the recently introduced Carpet Weaver Optimization (CWO) algorithm in solving the DG placement (DGP) problem.Inspired by the coordination between a carpet weaver and a map reader, CWO models their decision-making process to achieve an optimized pattern.This study presents the first application of CWO for determining the optimal locations and capacities of DG units in power networks.Extensive simulations are conducted on benchmark test systems to assess the performance of CWO in comparison with 12 well-established metaheuristic algorithms.The evaluation criteria include power loss minimization, voltage profile enhancement, and computational efficiency.The results demonstrate that CWO consistently outperforms all competitor algorithms, achieving superior convergence speed, solution accuracy, and stability in complex optimization scenarios.Statistical analyses validate the robustness of CWO in addressing the intricate nature of the DGP problem.The key contributions of this research include the first implementation of CWO in power system optimization, a comprehensive comparative analysis with 12 competitive algorithms, and an in-depth assessment of its adaptability for solving large-scale engineering problems.The findings establish CWO as a highly efficient and promising optimization technique for DG placement, offering improved network performance and operational reliability.