Multiobjective Optimal Power Flow Using a Semidefinite Programming-Based Model

In spite of the significant advance achieved in development optimal power flow (OPF) programs, most solution methods reported literature have considerable difficulties dealing with different-nature objective functions simultaneously. By leveraging recent progress on semidefinite programming (SDP) relaxations OPF, present article, attention is focused modeling a new SDP-based multiobjective OPF (MO-OPF) problem. The proposed model incorporates classical ?-constraint approach through parameterization strategy to handle multiple and produce Pareto front. This article emphasizes extension for MO-OPF problems generate globally nondominated solutions uniform distribution. Numerical results IEEE 30-, 57-, 118-bus, Indian utility 62-bus test systems all security operating constraints show that convex can no duality gap polynomial time, efficient set, outperform well-known heuristic generally used MO-OPF. For instance, comparison obtained NSGA-II 57-bus system, best compromise by SDP has 1.55% 7.42% less fuel cost transmission losses, respectively.