A hybrid model for the transient stability of the rotor angle constrained optimal power flow

Optimal power flow with transient stability is a nonlinear optimization problem with algebraic and differential equations. In this paper, using the imperialist competition algorithm as an evolutionary optimization algorithm and artificial neural network, a robust and effective two-stage design for solving the TSCOPF problem (transient stability constrained optimal power flow) has been proposed. In hybrid model, an artificial neural network was introduced to predict the transverse stability margin of the rotor angle and then to estimate the transient stability of the rotor angle bound to the optimal load distribution. To solve the problem of TSCOPF (transient stability constraint optimal power flow), imperialist competition algorithm optimization has been used. The function of the proposed method is based on the three-machine system, the WSCC (Western System Coordinating Council) and the IEEE cases under different loading conditions and error mode