Optimality-feasibility-aware multistage unit commitment considering nonanticipative realization of uncertainty

The intrinsic uncertainty in source-load power and line outage poses huge obstacles to unit commitment (UC) optimization in power grids. To satisfy the practical requests in power grids, this paper exploits a multistage robust UC method to promise both optimality and feasibility in nonanticipative scheduling. Firstly, a multistage robust UC model is established accounting for the sequential realization of uncertainty. This model makes de-cisions with the goals of economy in the normal condition and power balance in the emergent condition. Sec-ondly, a customized multi-cut decomposition algorithm is offered to address the intractable multistage robust optimization problem. The original multistage problem is decoupled into the form of one master and several slave problems (MP-SPs), where the robust dual dynamic programming (RDDP) solves the resulting multistage max-min SPs, and the column-and-constraint generation (C&CG) algorithm successively constructs multiple cutting planes to ensure the optimality and convergence of the alternative optimizations between the MP and SPs. Computational tests on real-size power grids validate the practicability and superiority of the proposed multistage robust UC method, which is of great significance in guiding system operations.