Optimal Configuration of Soft Open Points for Distribution Networks with High Penetration of Distributed Power Sources

Aiming at the problems of reverse power flow and voltage limit violations in distribution networks caused by the integration of high-proportion distributed power sources, this paper establishes a multi-objective optimal configuration model for soft open points (SOPs), taking a suburban distribution network as an example. The model balances the annual comprehensive cost and system operational performance. By using K-means clustering to construct multi-scenario power flow models, and employing a hybrid algorithm combining an improved particle swarm optimization (PSO) with second-order cone programming (SOCP), the optimal installation locations and capacities are determined. The results indicate that SOPs can effectively solve the problem of voltage limit violations at the end of feeders, significantly reduce the load imbalance among feeders, and enhance the renewable energy accommodation capability and power supply reliability of the distribution network.