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Transient stability constrained optimal power flow (TSC-OPF) is originally a nonlinear optimization problem with variables and constraints in time domain, which is not easy to deal with because of its huge dimension, especially for systems with detailed machine models. This paper presents an efficient approach to realize TSC-OPF by introducing an(More)
Critical clearing time (CCT) is an important parameter used in transient stability assessment of power systems. In this paper, only pre-fault generator voltage magnitudes and active powers are used as inputs to a multilayer feedforward neural network (MFNN) trained using Gauss-Newton approximation for Bayesian regularization to estimate the CCT in an(More)
Transient stability-constrained optimal power flow (TSC-OPF) aims at optimising the scheduling of generation with stability constraints to ensure a secure system in the event of contingencies. This paper proposes a new approach based on a critical clearing time (CCT) constraint that replaces the dynamic and transient stability constraints of the TSC-OPF(More)
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