Optimizing distributed generation sizing and siting using particle swarm optimization: A comparative study

Abstract

In recent years, distributed generation (DG) has become increasingly popular as a means of mitigating the impact of climate change and ensuring a reliable and resilient power supply. To optimize the use of DG, it is essential to determine the most effective DG sizing and siting for a given power system. This problem has been researched, and several heuristic algorithms have been proposed and tested. This paper focuses on applying particle swarm optimization (PSO) to this problem to minimize real power loss. Five different PSO variants in single and three DG unit scenarios using the IEEE 33 bus system are tested to reveal the efficiency of the variants and their potential for improving the solution's performance. By comparing the performance of the different PSO variants with the ones in the literature, we found that PSO outperformed other heuristic algorithms for this problem. Our findings highlight the importance of choosing the suitable optimization algorithm for DG sizing and siting to achieve the best possible outcomes for power systems operations.