Distributionally Robust Allocation of Energy Storage Integrated With Soft Open Points Coordinating Flexibility and Resilience

Abstract

The large-scale integration of renewable distributed generators (DGs) and the increasing frequency of extreme events have heightened the demand for enhanced flexibility and resilience in distribution networks. Energy storage integrated with soft open points (E-SOPs) can improve both flexibility and resilience temporally and spatially. This paper presents a distributionally robust optimisation with a hybrid ambiguity set (HASDRO) method for E-SOPs allocation, aiming to enhance renewable energy consumption and operation efficiency under normal scenarios, while ensuring load supply during extreme events. The proposed hybrid ambiguity set combines a Wasserstein metric-based ambiguity set to capture the probability distributions of DG output and load demand, and a first-order moment-based ambiguity set to represent line outages. A two-stage HASDRO model is then formulated to optimise the planning and operation of E-SOPs, and to minimise total investment and worst-case expected operation costs, including DG curtailment and line loss penalties in normal scenarios as well as load shedding penalties in extreme events. The proposed HASDRO model is reformulated into an equivalent three-level model and solved by the customised column-and-constraint generation algorithm. Finally, the proposed method is validated on a modified IEEE 33-bus system, with the optimal E-SOP configuration comprising an ESS of 1.5 MW / 2.74 MWh and SOPs of 2.1 MVA. The results demonstrate a 43.10% reduction in line losses a 56.15% decrease in DG curtailment in normal scenarios, and a 52.24% reduction in load shedding during extreme events, highlighting the model's effectiveness in enhancing network flexibility and resilience.