Non dominated sorting gravitational search algorithm based optimal power flow with emission and non smooth cost functions

This article presents application of non dominated sorting based gravitational search algorithm (NSGSA) for solving optimal power flow (OPF) problems with economic and environment objectives. Fast elitist non-dominated sorting and crowding distance have been used to locate and manage the Pareto optimal front. The proposed method is tested and implemented on standard IEEE 30-bus test power system, with different objectives, that reflect the minimization of total quadratic fuel cost, piecewise quadratic fuel cost, fuel cost with valve point loading effect of generators and emission cost. The numerical results have been compared with other recently developed algorithms to reveal the tangible superiority of the proposed method for solving the OPF problems.