| Abstract: | In modern industrialized societies, it is mandatory to provide an uninterrupted supply of high-quality electric energy at modest cost while promoting a better environment. This can only be realized through very sophisticated power system operations that compromise several contradictory factors, namely, economy, security and environment. Since these factors are in trade-off relationships to each other, they should be analyzed appropriately. One class of problems that simultaneously satisfy several criteria in trade-off relationships is called “multiobjective optimization problems.” Optimal power flow (OPF) has been regarded as the most powerful means to obtain effective system operation plans since it only optimizes a single objective function. This paper proposes an efficient solution methodology for a class of multiobjective optimal power flow problems which makes use of a heuristic search method. An optimal solution can be found in the proposed heuristic search method based on local information about a preference index, which is chosen arbitrarily from a given set of objectives. This circumvents the exhaustive evaluation of all noninferior solutions needed in the existing multiobjective OPF algorithm proposed by the authors, thus dramatically reducing the solution time. The proposed method has been coded and applied to the IEEE 57 node test system. Simulation results have demonstrated the possibility of utilizing this method in on-line environments. |
