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In this paper, we present decomposition techniques for solving large-scaleinstances of the security-constrained optimal power flow (SCOPF) problem withprimary response. Specifically, under each contingency state, we require thatthe nodal demands are met and that the synchronized units generating belowtheir limits follow a linear model for primary response. The resultingformulation is a mixed-integer linear program since the primary response modelintroduces disjunctions to the SCOPF problem. Unfortunately, exact methodsrelying on traditional Benders' decomposition do not scale well. As analternative, we propose a decomposition scheme based on thecolumn-and-constraint-generation algorithm where we iteratively adddisjunctions and cuts. We provide procedures for preprocessing dedicated cutsand for numerically determining the post-contingency responses based on themaster problem solutions. We also discuss heuristics to generate high-qualityprimal solutions and upper bounds for the method. Finally, we demonstrate theefficiency of the proposed method on large-scale systems.

An Exact and Scalable Problem Decomposition for Security-Constrained Optimal Power Flow