Enhancing Operational Efficiency in Active Distribution Networks: A Two-Stage Stochastic Coordination Strategy with Joint Dispatch of Soft Open Points and Electric Springs

Abstract

Emerging power electronic devices like soft open points (SOPs) and electric springs (ESs) play a vital role in enhancing active distribution network (ADN) efficiency. SOPs enable flexible active/reactive power control, while ESs improve demand-side management and voltage regulation. This paper proposes a two-stage stochastic programming model to optimize ADN’s operation by coordinating these fast-response devices with legacy mechanical equipment. The first stage determines hourly setpoints for conventional devices, while the second stage adjusts SOPs and ESs for intra-hour control. To handle ES nonlinearities, a hybrid data–knowledge approach combines knowledge-based linear constraints with a data-driven multi-layer perceptron, later linearized for computational efficiency. The resulting mixed-integer second-order cone program is solved using commercial solvers. Simulation results show the proposed strategy effectively reduces power loss by 42.5%, avoids voltage unsafety with 22 time slots, and enhances 4.3% PV harvesting. The coordinated use of SOP and ESs significantly improves system efficiency, while the proposed solution methodology ensures both accuracy and over 60% computation time reduction.