Optimization of Distribution Network Configurations in Emergency Projects Using an Improved Particle Swarm Algorithm

The management of distribution networks in emergency scenarios often demands rapid and efficient configuration to ensure reliability and performance. Traditional methods typically focus on financial aspects and expert-driven decision-making, which may not fully utilize the capabilities of modern computational techniques. This paper introduces an improved particle swarm optimization (PSO) algorithm, enhanced with a conjugate gradient method, to address the configuration challenges in emergency project distribution networks. By prioritizing technical performance metrics such as network reliability, load balancing, and operational efficiency, the algorithm seeks to optimize network configurations in real-time. The effectiveness of this approach is demonstrated through a case study involving a provincial emergency project grid, highlighting significant improvements in network performance and efficiency. This research shifts the focus from financial investment controls to a computational optimization perspective, offering a valuable tool for emergency management and technical operations planning.