A Novel Iterative Contingency Filtering Approach to Corrective Security-Constrained Optimal Power Flow

This paper proposes a novel iterative approach to contingency filtering for corrective security-constrained optimal power flow (CSCOPF) problems that include conflicting contingencies. The rescheduling index (the minimum of the maximal controllable rescheduling value in the post-contingency state) becomes the filtering index in a modified CSCOPF (MCSCOPF) model designed to deal with conflicting contingencies. Moreover, a decomposed parallel interior point method (DPIPM) is developed to factorize the primal-dual system into blocks according to contingency scenarios and compute these blocks with a coarse-grained parallelism. The feasibility and effectiveness of the proposed approach is verified by solving for conflicting contingencies in a standard testing system and a real-world system.