Title :
A multi-objective genetic algorithm approach to optimal allocation of multi-type FACTS devices for power systems security
Author :
Radu, D. ; Bésanger, Y.
Author_Institution :
LEG, ENSIEG, St. Martin d´´Heres
Abstract :
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
Keywords :
Pareto optimisation; flexible AC transmission systems; genetic algorithms; load flow; power system security; Pareto optimal frontier; flexible AC transmission system devices; load flow calculations; multiobjective genetic algorithm; multitype FACTS devices; power systems security; Flexible AC transmission systems; Genetic algorithms; Genetic engineering; Hybrid power systems; Information security; Investments; Power engineering and energy; Power generation economics; Power system economics; Power system security; FACTS devices; Pareto frontier; multi-objective genetic algorithms; optimal location;
Conference_Titel :
Power Engineering Society General Meeting, 2006. IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0493-2
DOI :
10.1109/PES.2006.1709202
