Corrective security-constrained optimal power flow (CSCOPF) considers the use of corrective control to remove system security violations in the post-contingency state. Its optimality not only depends on the pre-contingency state, but also the post-contingency state as well as the involved corrective control actions. This study first gives a comprehensive review on the relevant OPF models and then proposes a hybrid method to solve the CSCOPF problem. It makes use of the evolutionary algorithms to randomly search the maximum feasible region and state-of-the-art OPF solution technique (interior-point method) to provide deterministic solutions in the found region. The two interact iteratively to progressively approach the final solution. The proposed method is verified on the IEEE 14-bus and 118-bus systems. Comparison studies show that (i) CSCOPF can better balance the security and economy and (ii) the hybrid method is overall superior (in solution quality, robustness and convergence characteristic) over the single evolutionary algorithm. Parallel processing is applied to speed-up the computations. © The Institution of Engineering and Technology 2014.