Solving multi-contingency transient stability constrained optimal power flow problems with an improved GA

In this paper, an improved genetic algorithm has been proposed for solving multi-contingency transient stability constrained optimal power flow (MC-TSCOPF) problems. The MC-TSCOPF problem is formulated as an extended optimal power flow (OPF) with additional generator rotor angle constraints and is converted into an unconstrained optimization problem, which is suitable for genetic algorithms to deal with, using a penalty function. The improved genetic algorithm is proposed by incorporating an orthogonal design in exploring solution spaces. A case study indicates that the improved genetic algorithm outperforms the existing genetic algorithm-based method in terms of robustness of solutions and the convergence speed while the solution quality can be kept.