Hierarchical adaptive PSO for multi-objective OPF considering emissions based shunt FACTS

This paper presents a hierarchical adaptive particle swarm optimization (APSO) for multi objective optimal power flow considering emissions coordinated with dynamic control of shunt FACTS devices. This study introduces a new variant of PSO using new mechanism search based dynamic adjustment of PSO parameters coordinated with a hierarchical decomposed strategy to improve the performances of the original PSO in terms of solution quality and convergence characteristics. The proposed strategy have been successfully adapted and applied for solving the multi objective optimal power flow considering emissions, and practical generators constraints (valve point effect). The APSO algorithm optimizes simultaneously a combined control variables, active power generations, voltage generators, tap transformer and the reactive power of multi SVC Controllers installed at a specified buses to minimize fuel cost, emissions, total power loss and voltage profile while satisfying the generators constraints and power system security. The proposed approach have been examined and applied to the 6 generating units considering emissions, to the IEEE 57-Bus considering all security constraints, and to the 40 generating units with valve point effects. Simulation results compared to the standard PSO and other recent methods confirm the effectiveness of this new PSO variant.