Data-driven stochastic optimization for energy management in distribution network with soft open points

The high penetration of distributed generators and ubiquitous inverter-based resources plays a critical role in the optimal operation of distribution systems. This paper presents a data-driven stochastic optimization framework for optimal operation of soft-of-point (SOP) integrated distribution networks with active management schemes. Firstly, the optimal operation of SOPs in distribution networks is formulated as a network-constrained energy management problem; Subsequently, Gaussian process is integrated to enable an accurate representation of potential distribution of uncertainties. Ultimately, a stochastic optimization approach is introduced to address this uncertainty-aware network-constrained energy management. The numerical simulation results in 33-bus distribution networks demonstrate that the proposed approach has 1.06% improvement compared to the scenarios without SOPs. These results underscore the effectiveness and economic benefits of the proposed approach.