The Distribution Network Loss Minimization by Incorporating DG Using Particle Swarm Optimization (PSO) Technique

This research is based on the power system optimal planning and operation segment. This study presents a methodology for reducing power losses in distribution power systems through the incorporation of both fixed and uncertain photovoltaic (PV) generation, utilizing the Particle Swarm Optimization (PSO) technique. The proposed approach aims to address the unpredictability of PV generation and optimize the placement and size of Distributed Generation (DG) units to minimize I2R loss in the distribution network. The main focus is on how to minimize the existing losses occurring in the distribution system. In the distribution system the I2R loss amount is higher compared to the transmission system. The reason behind the high amount of I2R loss in the distribution system is due to the high ratio, high current and low voltage. To reduce these losses, several researchers provide solutions, such as network reconfiguration, capacitor allocation, DG allocation, and DSTATCOM allocation. In this research I have focused on DG allocation solution for reducing the I2R loss. I have determined the most suitable photovoltaic generation capacity and location to minimize power loss in the system using the PSO algorithm. The PSO techniques can accurately determine the optimal locations for PV generation in the IEEE-33 bus and IEEE-69 bus radial feeder, which preserves power quality for consumers and reduces energy loss during distribution. To conduct this study, three simulation scenarios were employed, namely: a) the base case, b) without accounting for the uncertainty of solar irradiance and load demand, and c) considering the uncertainty of solar irradiance and load demand. The comparison between the three scenario results will also be shown in the results section for both the IEEE-33 and IEEE-69 bus systems. MATLAB R2021a was utilized to evaluate the algorithm's effectiveness in the IEEE-33 and IEEE-69 bus systems