Multiobjective optimal network reconfiguration considering the charging load of PHEV

Energy crisis and environmental pollution make the electric vehicle (EV) become a hot topic. The connection of EVs to the power grid brings great challenges to the electric utilities. This paper proposes a multiobjective network reconfiguration methodology based on quantum-inspired binary particle swarm algorithm that aims at alleviating the adverse impact of plug-in hybrid electric vehicle (PHEV) on distribution system. The fuzzy sets are used to handle the multiobjective. The methodology involves two steps: load level division and network reconfiguration on each load level. Two different charging patterns of PHEV are considered in this analysis: uncoordinated charging and coordinated charging. The simulation results of a 33-bus distribution system show that the proposed methodology has a good effect on achieving the energy loss reduction and improving the voltage quality considering the charging load of PHEV.