• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2015, Vol. 37 ›› Issue (05): 967-973.

• 论文 • Previous Articles     Next Articles

An optimal charging schedule strategy of electric vehicles based
on partheno-genetic algorithm and dynamic programming  

LU Jianyi1,YAN Chao1,XIAO Laiyuan2,ZHENG Rui1   

  1. (1.School of Management,Huazhong University of Science and Technology,Wuhan 430074;
    2.School of Software Engineering,Huazhong University of Science and Technology,Wuhan 430074,China)
  • Received:2014-05-07 Revised:2014-09-09 Online:2015-05-25 Published:2015-05-25

Abstract:

Battery charging scheduling is one of the most important aspects in electric vehicle operations management. An efficient charging scheme can not only help operator reduce the charging cost but also relieve the stress of the power system during peak hours.Based on the assumptions of real time electricity price and nointerruption charging jobs,we propose a minimum charging cost strategy on the basis of parthenogenetic algorithm and dynamic programming.To test the performance,we make a comparison between our algorithm and a designed strategy called "first come first charge" and the traditional genetic algorithm.We test the three charging strategies with the same examples and the simulation results indicate that the proposed method is effective in cost saving while insuring the loading balance of the electric system.In addition,the Gantt chart of vehicle assignment also shows it can effectively relieve the stress of the grid.

Key words: electric vehicle;charge scheduling;partheno-genetic algorithm;dynamic programming