Distributed Robust Optimization Method for Active Distribution Network with Variable-Speed Pumped Storage

Abstract

Variable-speed pumped storage has the advantages of flexible adjustment and low economic cost, which can reduce the adverse effects caused by a high proportion of new energy access. In order to reduce the system operation risk caused by the randomness of new energy output, a distribution robust optimization method for an active distribution network with variable-speed pumped storage is proposed. Firstly, considering the probability distribution uncertainty of wind–solar prediction error, a two-stage distributed robust optimization model of an active distribution network is constructed with the sum of day-ahead operating cost, intra-day adjustment cost expectation and conditional value-at-risk as the objective function. Then, the probability distribution fuzzy set is constructed based on the norm distance, and the fuzzy set boundary is determined by a data-driven method. Finally, the model is transformed into a mixed integer second-order cone optimization model by a linearization method and duality theory, and verified by an example. The results show that the proposed model can effectively reduce the operation risk caused by the uncertainty of operating cost and wind–solar output and reduce the operational costs and the risks associated with uncertainty in wind and solar power output.