Distributed methods for solving the security-constrained optimal power flow problem

The optimal power flow is the problem of determining the most efficient, low-cost and reliable operation of a power system by dispatching the available electricity generation resources to the load on the system. Unlike the classical optimal power flow problem, the security-constrained optimal power flow (SCOPF) problem takes into account both the pre-contingency (base-case) constraints and post-contingency constraints. In the literature, the problem is formulated as a large-scale nonconvex nonlinear programming. We propose two decomposition algorithms based on the Benders cut and the alternating direction method of multipliers for solving this problem. Our algorithms often generate a solution, whose objective function value is smaller than conventional approaches.