A global approach to transient stability constrained optimal power flow using a machine detailed model

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 independent dynamics simulation algorithm into the optimization procedure. In the new approach, the simulation algorithm is used to realize the dynamic constraints and to deduce the transient stability constraint, while the optimization algorithm verifies the steady state and the transient stability constraints together. The new TSC-OPF has just one more constraint than that of a conventional OPF and can be solved by a conventional OPF algorithm with small modification. In the new approach, there is no limitation for the machine model and the simulation method. The nonlinearity of the power system is taken fully into account. In the paper, the proposed approach is verified with a small three-machines system. The simulation results show the machine model influences greatly the system transient stability and the TSC-OPF results. The widely used machine classical model in the TSC-OPF over-estimates the system transient stability and under-estimates the TSC-OPF costs.