Distributionally Robust Optimization-based Stochastic Operation Strategy of Soft Open Points in Distribution Networks

For the flexible operation of modern distribution networks that include an increasing number of renewable energy sources (RESs), this study proposes a stochastic operation method for a novel platform that combines energy storage with a power flow controller called multi-terminal soft open point (MT-SOP). Assuming a practical situation in which there is no prior knowledge about the distribution of forecast errors for load and RES output, a Wasserstein metric-based distributionally robust chance-constrained optimization for the operation of MT-SOP is proposed. The proposed method stochastically relaxes the reliability constraints on bus voltage, which maximizes the cost-benefit of the distribution system operator (DSO). With the relaxed operational model of MT-SOP, the proposed problem is reformulated into a tractable convex program by interpreting related state-of-the-art research. Based on case studies using modified IEEE-33 systems with variable types of forecast error distribution, we analyze the trade-off between cost benefits and risk levels on network voltage reliability. Numerical comparison of the simulation results shows that our proposed method for the DSO can achieve economic efficiency for imported electricity from external power grids by relaxing conservativeness on reliability.