Volume 2 - Issue 2, March - April 2026

This research investigates the optimization of electrical power distribution networks with the primary objective of minimizing active power losses and enhancing voltage profiles through intelligent network reconfiguration. The study focuses on the IEEE 33-bus and 69-bus radial distribution systems and employs the Grey Wolf Optimization (GWO) algorithm—a meta-heuristic inspired by the cooperative hunting behavior of grey wolves—to determine optimal switching configurations of sectionalized and tie switches while maintaining network reliability and radial topology constraints. The proposed GWO-based reconfiguration model incorporates multi-objective functions that simultaneously address active and reactive power loss reduction indices and voltage profile improvement indices. Power flow analyses are conducted using the Newton-Raphson method to validate system performance before and after reconfiguration. Simulation results reveal significant improvements: for the IEEE 33-bus system, active power loss is reduced by 23.83% and reactive power loss by 3.90%, while voltage magnitude improved from 0.9107 pu to 0.9212 pu. Similarly, for the IEEE 69-bus system, active and reactive power losses decreased by 46.99% and 5.35%, respectively, with the minimum voltage rising from 0.9091 pu to 0.9482 pu. The findings demonstrate that the GWO algorithm outperforms traditional optimization techniques in achieving rapid convergence, superior power loss minimization, and enhanced voltage stability. The study establishes GWO as a robust and computationally efficient tool for real-time distribution network reconfiguration, contributing to improved operational efficiency and loss mitigation within modern smart grid systems.

Muhammad Khurshid Ahmad, Muhammad Aslam1, Abdullah Khan,"Reduction of Losses in Energy Distribution by Reconfiguration of The Network Using New Optimization Technique" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(1016-1046) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.