Skip to Main Content
A hybrid method combining classical deterministic programming technique and evolutionary algorithm (EA)-enhanced stochastic optimization strategy is proposed for more effective and flexible computation of transient stability-constrained optimal power flow (TSC-OPF). The method consists of searching the maximum TSC-feasible solution region with EA and deterministically optimizing an operating point in the found region via a conventional OPF solution. Stability constraints are exactly treated by a rigorous transient stability assessment (TSA) procedure, where complex system model and multi-contingency can be readily considered and stability margin is applied as the transient stability index (TSI) to avoid over-stabilizing. Benefiting from both the EA and the deterministic programming, the proposed method can continuously approach the global optima in a robust, reliable and fast-convergent way. The method is verified on the New England test system and a dynamic equivalent system of a real-world large power grid. Comparing with existing methods, it has provided more economic solutions and better adaptability to multi-swing instability and multi-contingency stabilizing. It can also be a unified approach for solving other stability constrained-OPFs.