Objective With the large-scale integration of distributed energy resources such as wind and solar power, distribution networks are experiencing increasing operational challenges, including voltage violations, reverse power flows, and rising line losses. Soft open points (SOPs), as a new type of power electronic equipment, provide flexible power flow control and enhanced network controllability, making them a key solution for constructing flexible interconnected distribution networks. This paper addresses the configuration problem of SOPs under uncertainty in DG output and load variation.

Method A mixed-integer second-order cone programming (MISOCP) model was proposed to jointly optimize the location, sizing (as continuous variables), and multi-period power flow of SOPs. The model aimed to minimize the total cost, including SOP installation and operation costs as well as network line losses, while accounting for the temporal characteristics of load and the uncertainty of DG output. The proposed model was solved using the YALMIP toolbox and the Gurobi 12.0 solver.

Result Case studies on the IEEE 33-bus distribution system show that the proposed method reduces line losses by approximately 15% and lowers the SOP configuration cost by around 12%, while significantly improving voltage profiles and enhancing power quality. Compared with scenarios without SOPs, the optimized configuration also improves system economic efficiency and reliability.

Conclusion The proposed SOP planning and optimization method effectively balances operational cost and voltage regulation performance, demonstrating strong adaptability and practical value. It offers a viable solution for SOP configuration under high penetration of distributed generation, contributing to enhanced flexibility and renewable energy hosting capacity of distribution networks.