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Scalable Security-Constrained Unit Commitment Under Uncertainty via Cone Programming Relaxation

This paper is concerned with the problem of Security-Constrained Unit Commitment (SCUC) which is a long-standing challenge in power system engineering faced by system operators and utility companies on a daily basis. We consider a detailed variant of this problem that suffers from complexities posed by the presence of binary variables, the uncertainty of renewable sources and security constraints. A convex relaxation is formulated which is capable of finding feasible solutions within a provable distance from global optimality. We demonstrate the performance of this approach on detailed and challenging instances of SCUC with IEEE and PEGASE benchmark cases from Matpower . The proposed approach is able to handle over 12,000 binary variables and 2 million continuous variables with significant improvement in solution quality over commonly-used off-the-shelf solvers and other methods of convex relaxation.