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Security-constrained optimal power flow (SCOPF) is an important tool to optimize power system's operating state while satisfying security requirements with respect to credible contingencies. As a necessary extension to conventional SCOPFs, the recently proposed preventive–corrective SCOPF (PCSCOPF) aims to achieve the best coordination between the preventive control (PC) and corrective control (CC) considering the probabilistic nature of the contingencies and the cost of CC as well as other binding constraints. However, PCSCOPF renders a large-scale, multi-stage, non-linear programming problem which is difficult to directly solve. This paper proposes a novel and improved approach to the PCSCOPF problem. We aim to partition the contingencies into two exclusive sets: one is secured in the PC stage and the other in the corrective control CC stage. The PC corresponds to an ordinary SCOPF model and solved by the Benders decomposition method; the CC corresponds to an ordinary OPF model. The optimal partitioning of the contingencies is determined using an evolutionary algorithm (EA). Compared with the existing methods, the proposed approach is advantageous in that its searching dimension only depends on the number of insecure contingencies, hence tends to lead to a much higher solution speed. The proposed method is verified on the IEEE 118-bus system and compared with other two existing methods. Simulation results show that the proposed method can provide high-quality solutions with much higher computation speed. [ABSTRACT FROM AUTHOR]

• Proposing an energy-function-based approach to assess the transient stability of the economic operating point of the power system. • Developing a transient stability criterion to solve system swing equations only until the fault clearing time, that improves the computational efficiency of the transient stability constrained OPF problem significantly. • Utilizing Benders decomposition technique to handle the transient stability constraints as parallel and separate sub-problems. • Promoting the transient stability constrained Optimal Power Flow to estimates the system critical clearing time with an acceptable level of accuracy without any network reduction. Security Constrained Optimal Power Flow (SCOPF) is traditionally performed to obtain the optimal generation levels to achieve the minimum generation cost under operational constraints in normal and contingency conditions. In this paper the SCOPF problem with DC load flow equations is extended to consider the transient stability margin of the generating units as a heuristic decomposition algorithm. However, the proposed algorithm is compatible with any SCOPF formulation. Due to computational complexities of security constraints and transient stability assessment, Benders decomposition algorithm is utilized to handle the transient stability margin of generating units as separate sub-problems. A transient energy function is developed to assess the transient stability of generating units under credible faults using the cut-set energy function criterion. In case of violation of the required transient stability margin, Benders cuts are constructed and added to the master problem. The proposed decomposed Transient Stability Constrained OPF (TSCOPF) is converged in few iterations. The developed TSCOPF algorithm is implemented on the IEEE 39-bus dynamic test system to validate its accuracy and efficiency. [ABSTRACT FROM AUTHOR]