Transient stability constrained optimal power flow using teaching learning based optimization

Transient Stability Constrained Optimal Power Flow (TSCOPF) constitutes one of the most computational-intensive applications; it is used for power system preventive control against blackouts triggered by transient instability after a contingency. In this paper, a novel Optimal Power Flow (OPF) is proposed by adding the Transient Stability (TS) constraints into the conventional OPF problem, a Teaching-Learning-Based Optimization (TLBO) is proposed to solve the OPF problem. The objective function is to minimize the total cost of fuel for all generators. The proposed methodology has been tested on standard test systems the IEEE 30-bus network model. The simulation results are compared to those obtained with other conventional and new methods found in recent works.