Multi-objective particle swarm optimization algorithm-based method for optimal placement and sizing of distributed generations and shunt capacitors in a radial distribution network

作者：Pinank Patel, Nagaraj Patil, A. Mohsen, Aditya Kashyap, Nofal Adrees Hasan, Athikkattuvalasu S. Karthikeyan, Dhirendra Nath Thatoi, Deepak Gupta, Alireza kamranfar · 发表于：Results in Engineering · 年份：2025 · DOI：10.1016/j.rineng.2025.106514 · 被引用次数：19 · 研究领域：Optimal Power Flow Distribution、Microgrid Control and Optimization、Electric Power System Optimization

One of the most effective methods for responding to load growth and ensuring a specific level of reliability in power distribution networks is the use of renewable energy resoureces. Various technologies, such as photovoltaic cells, wind turbines, combustion engines, and fuel cells, can be utilized as DG sources, depending on geographic suitability. These distributed generations (DGs) sources are directly connected to the distribution network, with capacities ranging from a few kilowatts to 10 megawatts. This paper presents a method for the optimal placement and sizing of DG and shunt capacitors in radial distribution systems, considering both simultaneous and independent placements as a multi-objective problem. The objective function, which includes power losses, voltage profile enhancement, and related costs, is optimized through the Multi-Objective Particle Swarm Optimization (MOPSO) method. Simulations are performed in MATLAB/Simulink software, and finally, the results are evaluated on the standard IEEE 69-bus network, demonstrating the impact of DG and capacitors on network performance. Simulation results shows that the proposed method achieved a 94.8 % reduction in power losses and improved the voltage stability index to 0.9745 pu in the IEEE 33-bus test system.