On Affine Policies for Wasserstein Distributionally Robust Unit Commitment

his paper proposes a unit commitment (UC) model based on data-driven Wasserstein distributionally robust optimization (WDRO) for power systems under uncertainty of renewable generation as well as its tractable exact reformulation. The proposed model is formulated as a WDRO problem using an affine policy, which nests an infinite-dimensional optimization problem and satisfies the non-anticipativity constraint. To reduce conservativeness, we develop a novel technique that defines a subset of the uncertainty set with a probabilistic guarantee. Subsequently, the proposed model is recast as a semi-infinite programming problem that can be efficiently solved using existing algorithms. Notably, the scale of this reformulation is invariant with sample size. As a result, samples can be easily incorporated without using a sophisticated decomposition algorithm regardless of their number. Numerical simulations on 6- and 24-bus test systems demonstrate the economic and computational efficiency of the proposed model.