Optimization Strategy for Flexible Network Equipment Deployment Based on Multi-objective Collaboration and Adaptive Particle Swarm Optimization Algorithm

With the rapid development of renewable energy and electric vehicles, the safe operation of traditional distribution networks is facing challenges, and flexible distribution networks are of great significance in improving their economy and reliability. This article proposes a flexible network equipment layout optimization strategy based on multi-objective collaboration and adaptive particle swarm optimization algorithm. A dual objective optimization model with total economic cost and elastic improvement is constructed, considering constraints such as power flow balance and equipment operation. The particle swarm algorithm with adaptive adjustment of inertia weight is used to solve the problem. The simulation of a 20 node distribution network shows that this strategy can optimize the distribution points at key nodes, reducing the average load reduction to $28 \%$ and the average voltage deviation to $1.2 \%$, effectively improving the reliability and stability of the distribution network. This study provides an optimization method for the deployment of flexible network equipment, which is of great value for the intelligent and flexible development of distribution networks and the transformation of energy systems.