Particle Swarm Optimization Based Optimal Distributed Generation Placement and Sizing in Radial Distribution Network

This paper presents a Particle Swarm Optimization (PSO)–based approach for the optimal placement and sizing of multiple distributed generation (DG) units in a radial distribution network. The objective is to minimize total real power losses while improving the voltage profile, subject to system operating constraints. A backward–forward sweep (BFS) load flow algorithm is integrated with PSO to accurately model power flow in radial systems. Unlike conventional methods that fix the number or capacity of DG units, the proposed method simultaneously determines the optimal number, locations, and sizes of DGs without predefined restrictions. The methodology is tested on the IEEE 33-bus radial distribution system using MATLAB and validated with ETAP 2021. Simulation results demonstrate a significant reduction in real power losses and notable voltage profile enhancement. Specifically, the optimized allocation of three DG units achieves a loss reduction of approximately 47.05% and raises the minimum bus voltage close to nominal limits. The close agreement between MATLAB and ETAP results confirms the effectiveness and robustness of the proposed PSO-based optimization framework.