A multi-objective genetic algorithm approach to optimal allocation of multi-type FACTS devices for power systems security

A multi-objective programming procedure is used for solving the problem of optimal allocation of flexible AC transmission systems (FACTS) devices in a power system. The evolutionary approach consists of a multi-objective genetic algorithm (MOGA), which is used to characterize the Pareto optimal frontier (non-dominated solutions) and to provide to decision makers and engineers insightful information about the trade-offs to be made. In this paper, two technical and economical objective functions are considered: maximization of system security and minimization of investment cost for FACTS devices. The optimization process is focused on three parameters: the location of FACTS in the network, their types and their sizes. For these proposals, we employed a hybrid software developed in Matlabtrade which uses the EUROSTAGtrade software for load flow calculations. The proposed procedures are successfully tested on an IEEE 14-bus power system for several numbers of FACTS devices