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Adaptive robust unit commitment model based on the polyhedral uncertainty set

To address the increase of wind power uncertain along with wind power capacity, a bi-level robust unit commitment (RUC) model is built to obtain the optimal unit commitment scheme in the worst-case scenario. The objective function considers the start-up/off cost and operation cost of all units. Considering the temporal correlation characteristics of wind power forecast errors, a polyhedral uncertainty set is designed. Conditional Value-at Risk (CVaR) is adopted to describe the risk loss when the real wind power output is beyond the predefined uncertainty set and also determine the interval of acceptable wind power output. In view of the inner and outer layers of model interact with each other, the primal problem is decomposed into day-ahead UC master problem and the sub-problem which considers economic dispatch. In the solving process, the strong duality theorem and the Big-M method are employed to transform the sub-problem with max-min structure into a MILP problem, then the problem is solved by the column and constraint generation (C&CG) algorithm. Finally, the results show the effectiveness of the proposed model.