Dynamic strategy based fast decomposed GA coordinated with FACTS devices to enhance the optimal power flow

Under critical situation the main preoccupation of expert engineers is to assure power system security and to deliver power to the consumer within the desired index power quality. The total generation cost taken as a secondary strategy. This paper presents an efficient decomposed GA to enhance the solution of the Optimal Power Flow (OPF) with non-smooth cost function and under severe loading conditions. At the decomposed stage the length of the original chromosome is reduced successively and adapted to the topology of the new partition. Two sub problems are proposed to coordinate the OPF problem under different loading conditions: the first sub problem related to the active power planning under different loading factor to minimize the total fuel cost, and the second sub problem is a reactive power planning designed based in practical rules to make fine corrections to the voltage deviation and reactive power violation using a specified number of shunt dynamic compensators named Static Var Compensators (SVC). To validate the robustness of the proposed approach, the proposed algorithm tested on IEEE 30-Bus, 26-Bus and IEEE 118-Bus under different loading conditions and compared with global optimization methods (GA, EGA, FGA, PSO, MTS, MDE and ACO) and with two robust simulation packages: PSAT and MATPOWER. The results show that the proposed approach can converge to the near solution and obtain a competitive solution at critical situation and with a reasonable time. Key Words— Decomposed Network, Parallel Genetic Algorithm, System loadability, FACTS, SVC, Optimal power flow, System security, Planning and control. Dynamic Strategy Based Fast Decomposed GA Coordinated with FACTS devices to enhance the Optimal Power Flow Belkacem Mahdad1, Tarek Bouktir2, Kamel Srairi1 and Mohamed Benbouzid 3 1University of Biskra / Department of Electrical Engineering, Biskra (07000), Algeria 2 Oum El Bouaghi / Department of Electrical Engineering, Oum El Bouaghi, 04000, Algeria 3 University of Brest, EA 4325 LBMS, Rue de Kergoat, CS 93837, 29238 Brest Cedex 03, France