Multi objective optimal power flow using NSMOGSA

Application of non dominated sorting multi objective gravitational search algorithm (NSMOGSA) for solution of different optimal power flow (OPF) problem is presented in this article. NSMOGSA is an extension of the gravitational search algorithm (GSA), where the gravitational acceleration is updated using non-dominated sorting concept. A mixture of sign and reordering mutations are also proposed in to reduce the chance of trapping in local optima. The proposed method is employed for optimal adjustments of the power system control variables which involve both continuous and discrete variables of the OPF problem. To show the effectiveness of the proposed algorithm, it has been tested on a standard IEEE 30-bus system with two different individual objectives that reflect total emission cost minimization and fuel cost minimization. The performance of NSMOGSA is compared with the results found by other meta-heuristic techniques reported in the recent literature to demonstrate the tangible superiority of the proposed method.