Optimizing Power Losses and Voltage Profiles through Simultaneous Distribution Network Reconfiguration and DG Placement Using a Hybrid CDOA-PSO Algorithm

The optimal utilization of distribution networks through network reconfiguration has become increasingly critical in modern power systems, primarily due to the extensive integration of Distributed Generation (DG) resources. Strategically positioning and scaling distributed generation optimizes the equilibrium of energy provision and consumption, diminishes electrical losses, and elevates the voltage profile. Previous studies have predominantly concentrated on either DG optimization or distribution network reconfiguration, with limited research conducted on their simultaneous application. Therefore, this paper employs three meta-heuristic algorithms: the Collective Decision-Based Optimization Algorithm (CDOA), Particle Swarm Optimization (PSO), and a hybrid optimization algorithm termed CDOA-PSO, to concurrently address network reconfiguration alongside the optimal placement and sizing of DG. The suggested technique is applied to a 33-bus radial distribution network as per IEEE standards, utilizing MATLAB for execution. To assess the efficacy of the technique, six unique scenarios have been utilized. The results clearly demonstrate a substantial enhancement in the voltage profile and a decrease in power losses with the hybrid algorithm (CDOA-PSO) compared to both CDOA and PSO.