Optimal Allocation of Changing Station for Electric Vehicle Based on Queuing Theory

  • Yagang Zhang North China Electric Power University
  • Dingli Qi North China Electric Power University
  • Wei Jiang North China Electric Power University
  • Shuang Lei North China Electric Power University
Keywords: electric vehicle, charging station, centralized charging station, grey system model, queuing theory,


Electric vehicle as the main development direction of the future automotive industry, has gained attention worldwide. The rationality of the planning and construction of the power station, as the foundation of energy supply, is an important premise for the development of electric vehicles. In full consideration of the electric demand and electricity consumption, this paper proposes a new construction mode in which charging station and centralized charging station are appropriately combined and presents a location optimization model. Not only can this model be applied to determine the appropriate location for the power station, but it can use the queuing theory to determine the optimal number of power equipment, with which we can achieve the minimum costs. Finally, taking a certain city as an example, the optimum plan for power station is calculated by using this model, which provides an important reference for the study of electric vehicle infrastructure planning.

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Yagang Zhang, North China Electric Power University
University of South Carolina, Department of Mathematics and Interdisciplinary Mathematics InstituteColumbia, SC 29208, United States
Dingli Qi, North China Electric Power University
North China Electric Power UniversityDepartment of Mathematics and Physics, Baoding, 071003, P.R. China
Wei Jiang, North China Electric Power University
North China Electric Power University Department of Mathematics and Physics Baoding, 071003, P.R. China
Shuang Lei, North China Electric Power University
North China Electric Power UniversityDepartment of Mathematics and PhysicsBaoding, 071003, P.R. China


Han SP, Sam P, Marko P. Effect of hydrogen addition on criteria and greenhouse gas emissions for a marine diesel engine. International Journal of Hydrogen Energy. 2014;39(21):11336-11345.

Hakob GA, Elise MH, Suvish M. Effects of vehicle technologies, traffic volume changes, incidents and work zones on greenhouse gas emissions production. Transportation Research. 2014;26(1):10-19.

Zoran L, Eduard M, Rudolf T. The relevance of GHG emissions from motor vehicles. Transactions of FAMENA. 2013;37(2):39-56.

Florian K, Johannes L. Greenhouse gas reduction in transport: analyzing the carbon dioxide performance of different freight forwarder networks. Journal of Cleaner Production. 2015;99(7):177-191.

Chang CC. Advances in Electric vehicles. HKIE transaction. 2014;10(1):1-13.

Song YH, Yang YX, Hu Z. Present status and development trend of batteries for electric vehicles. Power System Technology. 2011;35(4):1-7.

Johannes H, Erik W, Warren S. Comparing the Mass, Energy and cost effects of Lightweighting in conventional and electric passenger vehicles. Journal of Sustainable Development of Energy, Water and Environment Systems. 2014;2(3):284-295.

Lunz B, Sauer DU. Electric road vehicle battery charging systems and infrastructure. Advances in Battery Technologies for Electric Vehicles; 2015.

Paul DL, Jairo V, Robert VP, Arne E. Consumer attitudes about electric cars: Pricing analysis and policy implications. Transportation Research Part A: Policy and Practice. 2014;69(11):299-314.

Amela A. Promoting Environmentally Benign Electric Vehicles. Energy Procedia. 2014;57(3):807-816.

Kou LF, Liu Z, Zhou H. Modeling Algorithm of charging station planning for regional electric vehicle. Modern Electric Power. 2010;27(4):44-48.

Du A, Hu Z, Song Y, Wu JY. Distribution network planning considering layout optimization of electric vehicle charging stations. Power system technology. 2011;2(11):35-42.

Raviv T. The battery switching station scheduling problem. Operations Research Letters. 2012;6(40):546-550.

Ge SY, Feng L, Liu H. The planning of electric vehicle charging station based on grid partition method. International Conference on Electrical and Control Engineering; 2011.

Li RQ, Su H. Optimal allocation of charging facilities for Electric Vehicles based on queuing theory. Automation of Electric Power Systems. 2011;35(14):58-61.

Wu CY, Li CB, Du L. A method for electric vehicle charging infrastructure planning. Automation of Electric Power Systems. 2010;34(24):36-39.

Tian L, Shi S, Jia Z. A statistical model for charging power demand of electric vehicles. Power System Technology. 2010;34(11):126-130.

Maršanić R, Zenzerović Z, Mrnjavac E. Planning model of optimal parking area capacity. Promet – Traffic & Transportation. 2010;22(6):449-457.

China. Quality and technical supervision bureau. Electric vehicle power supply and the technical specification - charging stations. DB/11. Beijing: The state council; 2010.

Zhang JY, Yu BY, Makoto C. Interdependences between household residential and car ownership behavior: a life history analysis. Journal of Transport Geography. 2014;34(1):165-174.

Glowacz A, Glowacz A, Glowacz Z. Recognition of thermal images of direct current motor with application of area perimeter vector and Bayes classifier. Measurement Science Review. 2015;15(3):119-126.

Glowacz A. Diagnostics of synchronous motor based on analysis of acoustic signals with the use of line spectral frequencies and k-nearest neighbor classifier. Archives of Acoustics. 2014;39(2):189-194.

Chang X. Guangzhou private ownership based on the GM model prediction and policy recommendations. Market Modernization. 2010;33(5):123-124.

How to Cite
Zhang Y, Qi D, Jiang W, Lei S. Optimal Allocation of Changing Station for Electric Vehicle Based on Queuing Theory. Promet [Internet]. 2016Nov.2 [cited 2024Jun.23];28(5):497-05. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/1974