Multi-Stage Robust Optimization of Real-Time Dynamic Dispatch With Fast-Acting Units in Resilient Power Systems

We propose a dynamic programming (DP) model for multi-stage stochastic-robust optimization (DMSR) to solve the real-time dispatch in power grids with fast-acting (FA) units for enhancing system resilience under extreme events. The proposed approach considers an offline solution and online dispatch. In the offline solution, the T-period real-time dispatch is formulated as a T-stage DMSR model, where its solution is based on an enhanced version of the fast robust dual dynamic programming (FRDDP) algorithm. In online dispatch, the mature cost-to-go functions coupling each stage are used as per-period policies to quickly direct the state adjustment of FA units and real-time dispatch decisions. In DMSR, the scenario-based technique is employed to model contingencies in the multi-stage framework, and the uncertainty set of wind power is constructed to reduce computing complexity. Case studies on the modified IEEE 14-Bus, 118-Bus and 300-Bus systems demonstrate the effectiveness of the proposed real-time dispatch method and solution methodology.