Affiliations: Department of Electrical Engineering, MSE Laboratory, Biskra University, Algeria | University of Brest, Brest, France
Note: [] Corresponding author. Belkacem Mahdad, Department of Electrical Engineering, Laboratory of Modelling Energetic Systems, Biskra University, Algeria. E-mail: bemahdad@mselab.org
Abstract: This paper presents a hierarchical interactive particle swarm optimization (HIPSO) for solving the static multi objective optimal power flow (OPF) considering multi SVC controllers and dynamic economic dispatch (DED). This study introduces a variant of PSO using new mechanism search based dynamic adjustment of PSO parameters coordinated with a hierarchical strategy for reactive power planning stage to improve the performances of the original PSO in terms of solution quality and convergence characteristics. The HIPSO algorithm optimizes a combined control variables such as: active power generations, voltage control of generators, tap transformer and the reactive power of multi SVC Controllers installed at a specified buses to minimize fuel cost, total power loss and voltage deviation while satisfying the generators constraints and power system security. The proposed approach examined and applied to many practical test systems: IEEE 57-Bus, IEEE 118-Bus, 40 generating units and 10 generating units to solving; the static multi objective OPF with quadratic fuel cost function, the economic dispatch considering valve point effects and the dynamic economic dispatch considering both valve point effects and ramp rate limits. Simulation results compared to Matpower, to the standard PSO and others recent metaheuristic methods confirm the effectiveness of the proposed combined approach.
Keywords: Hierarchical interactive PSO, multi-objective, optimal power flow, dynamic economic dispatch, voltage deviation, FACTS
