Active Distribution Networks Based on Improved Multi-objective Particle Swarm Algorithms for Locating and Determining the Capacity of Energy Storage System

Abstract

This paper proposes a multi-objective particle swarm optimization (MOPSO) algorithm for optimizing the placement of energy storage systems in active distribution networks to accommodate the integration of renewable energy sources such as solar and wind. Simulation analysis will demonstrate the algorithm's effectiveness in optimizing power distribution, reducing losses, and maintaining voltage stability in a dynamic energy environment, focusing on improving grid stability and efficiency. The algorithm considers the intermittent nature of renewable energy sources and strategically places energy storage systems to mitigate these fluctuations. By optimizing the placement of energy storage batteries, the algorithm not only improves the reliability and resilience of the grid but also makes more efficient use of renewable energy sources. Simulation results validate the algorithm's performance, with significant improvements in critical targets compared to previous approaches. In conclusion, this study provides a comprehensive solution for integrating renewable energy sources into distribution networks to ensure stability and reliability.