LAUSR

A virtual energy storage (VES) model is proposed in this paper to accommodate renewable energy under a special market regula-tion. Such VESs can provide or consume electricity to the main power grid under the premise that the daily net electricity energy is balanced. Furthermore, a multi-stage distributionally robust optimization (MSDRO) model is set up in this paper to address the temporal uncertainties in the day-ahead economic dispatch model. Compared with the traditional two-stage distributionally robust optimization, the proposed multi-stage approach provides more flexibilities so that the decision variables can be adjusted at each time period, leading to a complex nested formulation. To efficiently solve the MSDRO model, a stochastic dual dynamic programming is employed to decompose the original large-scale optimization model into several sub-problems in the stages, as two steps: forward pass and backward pass. In the forward pass, the expected cost-to-go function is approximated by piece-wise-linear functions and then several samples are used to gener-ate a lower bound; the backward pass will generate Benders cuts at each stage from the solution of the forward pass. The forward and backward passes are performed iteratively until the conver-gence is reached. Numerical results on an IEEE 118-bus system and a practical power system in China verify the proposed method.