Multi-objective configuration method for series compensation devices based on source-grid coordinated optimization under renewable energy integration

Abstract With the large-scale integration of renewable energy into power grids, its impact on system voltage stability has become increasingly significant, posing potential threats to grid security. While deploying series compensation (SC) devices can effectively enhance transmission capacity, achieving optimal SC configuration to maximize their efficacy remains a critical technical challenge. This study proposes a power system SC optimization method based on a random-weight Particle Swarm Optimization (PSO) algorithm. First, an in-depth analysis of power flow distribution is conducted after SC integration. Second, a multi-objective optimization model for SC configuration is established, considering voltage stability enhancement, transmission loss reduction, and cost-effectiveness. Finally, the model is solved using the random-weight PSO algorithm. Simulation tests on the IEEE 30-bus system demonstrate that optimized SC capacity allocation and placement significantly improve voltage quality and reduce network losses by 12.7% compared to conventional configurations. This research provides a robust solution for SC sizing and siting in power systems, offering both theoretical guidance and practical value for grid planning and operation.