Genetic Algorithm and Fuzzy Rules Applied to Enhance the Optimal Power Flow with Consideration of FACTS
Belkacem Mahdad, Tarek Bouktir, Kamel SrairiAbstract: In this paper an hybrid Genetic Algorithm and Fuzzy Logic rules is proposed to minimize the generator fuel cost with multi shunt Flexible AC Transmission Systems (FACTS). The problem is decomposed into, the optimal power generation subproblem that is searched by Genetic Algorithm and a simple practical reasoning fuzzy rules subproblem to control the reactive power exchanged with the network. The proposed method guarantees the near optimal solution and remarkably reduces the computation time. A global database generated based in reactive index sensitivity (RIS) as a flexible tool to choose economically the size of the shunt FACTS devices. This proposed approach is implemented with Matlab program with various case studies, and compared with conventional method, genetic algorithm (GA), ant colony optimization (ACO) and to the combined GA-Fuzzy based approach. The results show that the HGF can converge to the optimum solution in competitive with other methods, and obtains the solution with accuracy.
Keywords:
Optimal power flow, Economic dispatch(ED), genetic algorithm, Hybrid method, constrained optimization, heuristic optimization te
doi:10.5019/j.ijcir.2004.141
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