Multiobjective Distribution Network Reconfiguration Considering the Charging Load of PHEV

Energy crisis and environmental pollution make the plug-in hybrid electric vehicle (PHEV) become a hot topic. This paper proposes a multiobjective network reconfiguration methodology based on quantum-inspired binary particle swarm algorithm that aims at alleviating the adverse impact of PHEV on distribution system. The methodology involves two steps: load level division and network reconfiguration for each load level. Two different charging patterns of PHEV are considered in this analysis: uncoordinated charging and coordinated charging. The simulation results show that the proposed methodology is an effective method to make the distribution network more flexible to accommodate PHEV.DOI: http://dx.doi.org/10.5755/j01.eee.19.5.1738

[1]  Ying-Tung Hsiao,et al.  Multiobjective evolution programming method for feeder reconfiguration , 2004 .

[2]  Sanjoy Das,et al.  An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration , 2007 .

[3]  D. Das A fuzzy multiobjective approach for network reconfiguration of distribution systems , 2006, IEEE Transactions on Power Delivery.

[4]  J. Driesen,et al.  The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid , 2010, IEEE Transactions on Power Systems.

[5]  Mohammad A. S. Masoum,et al.  Real-Time Coordination of Plug-In Electric Vehicle Charging in Smart Grids to Minimize Power Losses and Improve Voltage Profile , 2011, IEEE Transactions on Smart Grid.

[6]  J. Z. Zhu,et al.  Optimal reconfiguration of electrical distribution network using the refined genetic algorithm , 2002 .

[7]  Ying-Yi Hong,et al.  Determination of network configuration considering multiobjective in distribution systems using genetic algorithms , 2005 .

[8]  Jong-Bae Park,et al.  A New Quantum-Inspired Binary PSO: Application to Unit Commitment Problems for Power Systems , 2010, IEEE Transactions on Power Systems.

[9]  Amit Kumar Tamang Coordinated Charging of Plug-in Hybrid Electric Vehicles to Minimize Distribution System Losses , 2013 .

[10]  Z. S. Xu,et al.  An overview of operators for aggregating information , 2003, Int. J. Intell. Syst..

[11]  A. Ahuja,et al.  An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration , 2007, IEEE Transactions on Power Systems.

[12]  Robert C. Green,et al.  The impact of plug-in hybrid electric vehicles on distribution networks: a review and outlook , 2010, IEEE PES General Meeting.

[13]  Yue Yuan,et al.  Modeling of Load Demand Due to EV Battery Charging in Distribution Systems , 2011, IEEE Transactions on Power Systems.