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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  2/2018 - 2

 HIGH-IMPACT PAPER 

Efficient Placement of Electric Vehicles Charging Stations using Integer Linear Programming

MILJANIC, Z. See more information about MILJANIC, Z. on SCOPUS See more information about MILJANIC, Z. on IEEExplore See more information about MILJANIC, Z. on Web of Science, RADULOVIC, V. See more information about  RADULOVIC, V. on SCOPUS See more information about  RADULOVIC, V. on SCOPUS See more information about RADULOVIC, V. on Web of Science, LUTOVAC, B. See more information about LUTOVAC, B. on SCOPUS See more information about LUTOVAC, B. on SCOPUS See more information about LUTOVAC, B. on Web of Science
 
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Download PDF pdficon (1,300 KB) | Citation | Downloads: 1,522 | Views: 4,996

Author keywords
charging stations, electric vehicles, integer linear programming, optimization, path planning

References keywords
electric(21), vehicle(14), charging(13), optimal(11), vehicles(9), stations(9), research(9), transportation(8), planning(8), hybrid(8)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-05-31
Volume 18, Issue 2, Year 2018, On page(s): 11 - 16
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.02002
Web of Science Accession Number: 000434245000002
SCOPUS ID: 85047873107

Abstract
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This paper presents an efficient optimization approach for the placement of electric vehicles charging stations within the road network. The approach is based on the integer linear programming technique for solving optimization problems. In this paper, the optimization problem is formulated as complex combinatorial problem with goal to find minimum number of strategically selected locations for charging stations which will enable covering of the route between each two nodes of the road network. The necessary input data are the road network configuration with distances and adopted electric vehicle autonomy. The input data are used for creation of the graph representing the road infrastructure with nodes as potential locations for charging stations. The application of proposed approach is demonstrated on example road configuration with emphasis on its scalability, generality and processing cost.


References | Cited By  «-- Click to see who has cited this paper

[1] R. Hoogma, R. Kemp, J. Schot, B. Truffer, "Experimenting for Sustainable Transport: The Approach of Strategic Niche Management", pp. 36-49, Spon Press, 2002.

[2] A. Y. Saber, G. K. Venayagamoorthy, "One million plug-in electric vehicles on the road by 2015," in Proc. 12th Int. IEEE Conf. Intell. Transp. (ITSC), St. Louis, MO, USA, 2001, pp. 141-147.
[CrossRef] [SCOPUS Times Cited 97]


[3] J. Smart, J. Franckfort, D. Karner, M. Kirkpatrick, S. White, "U.S. Department of Energy - Advanced vehicle testing activity: Plug-in hybrid electric vehicle testing and demonstration activities," in Proc. EVS24 International Battery, Hybrid and Fuel Cell Electric Vehicle Symposium, Stavanger, Norway, 2009, pp. 1-12.

[4] A. Hajimiragha, C. A. Caizares, M. W. Fowler, A. Elkamel, "Optimal transition to plug-in hybrid electric vehicles in Ontario, Canada, considering the electricity-grid limitations," IEEE Transactions on Industrial Electronics, vol. 57, no. 2, pp. 690-701, Feb. 2010.
[CrossRef] [Web of Science Times Cited 216] [SCOPUS Times Cited 283]


[5] A. H. Hajimiragha, C. A. Canizares, M.W. Fowler, S. Moazeni, and A. Elkamel, "A robust optimization approach for planning the transition to plug-in hybrid electric vehicles," IEEE Transactions on Power Systems, vol. 26, no. 4, pp. 2264-2274, Nov. 2011.
[CrossRef] [Web of Science Times Cited 129] [SCOPUS Times Cited 145]


[6] International Energy Agency, "Global EV outlook 2017 - Two million and counting", 2017.

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[8] G. Pistoia, "Electric and Hybrid Vehicles: Power Sources, Models, Sustainability, Infrastructure and the Market", pp. 517-542, Elsevier, 2010.

[9] I. Rahman, P. M. Vasant, B. S. M. Singh, M. Abdullah-Al-Wadud, N. Adnan, "Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures," Renewable and Sustainable Energy Reviews, vol. 58, pp. 1039-1047, May 2016.
[CrossRef] [Web of Science Times Cited 258] [SCOPUS Times Cited 318]


[10] S. Ge, L. Feng, H. Liu, "The planning of electric vehicle charging station based on Grid partition method," in Proc. International Conference on Electrical and Control Engineering, Yichang, China, 2011, pp. 2726 - 2730.
[CrossRef] [SCOPUS Times Cited 167]


[11] N. Shahraki, H. Cai, M. Turkay, M. Xu, "Optimal locations of electric public charging stations using real world vehicle travel patterns," Transportation Research Part D: Transport and Environment, vol. 41, pp. 165-176, Dec. 2015.
[CrossRef] [Web of Science Times Cited 207] [SCOPUS Times Cited 238]


[12] J. Dong, C. Liu, Z. Lin, "Charging infrastructure planning for promoting battery electric vehicles: an activity-based approach using multiday travel data," Transportation Research Part C: Emerging Technologies, vol. 38, pp. 44-55, Jan. 2014.
[CrossRef] [Web of Science Times Cited 390] [SCOPUS Times Cited 469]


[13] F. He, D. Wu, Y. Yin, Y. Guan, "Optimal deployment of public charging stations for plug-in hybrid electric vehicles," Transportation Research Part B: Methodological, vol. 47, pp. 87-101, Jan. 2013.
[CrossRef] [Web of Science Times Cited 397] [SCOPUS Times Cited 467]


[14] N. Sathaye, S. Kelley, "An approach for the optimal planning of electric vehicle infrastructure for highway corridors," Transportation Research Part E: Logistics and Transportation Review, vol. 59, pp. 15-33, Nov. 2013.
[CrossRef] [Web of Science Times Cited 125] [SCOPUS Times Cited 156]


[15] Z. Tang, C. Guo, P. Hou, Y. Fan, D. Jia, "Optimal planning of electric vehicle charging stations location based on hybrid particle swarm optimization," Advanced Materials Research, vol. 724-725, pp. 1355-1360, Aug. 2013.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 5]


[16] Z. Li, C. Guo, J. Chen, Z. Tang, W. Chen, Y. Wang, X. Li, Q. Ou, "A two-step method of optimal planning for electric vehicle charging stations location," Advanced Materials Research, vol. 953-954, pp. 1338-1341, Jun. 2014.
[CrossRef] [SCOPUS Times Cited 2]


[17] N. Rastegarfar, B. Kashanizadeh, M. Vakilian, S. A. Barband, "Optimal placement of fast charging station in a typical microgrid in Iran," in Proc. 10th International Conference on the European Energy Market (EEM), Stockholm, Sweden, 2013, pp. 1 - 7.
[CrossRef] [SCOPUS Times Cited 19]


[18] M. Hosseini, S. A. MirHassani, "Selecting Optimal Location for Electric Recharging Stations with Queue," KSCE Journal of Civil Engineering, pp. 1-10, Mar. 2015.
[CrossRef] [Web of Science Times Cited 45] [SCOPUS Times Cited 45]


[19] G. Chen, Z. Song, P. Dai, Y. Liu, Y. Ma, "Study on multi-objective optimal planning of electric vehicle charging stations with alternative sites," Advanced Materials Research, vol. 1070-1072, pp. 1656-1663, Dec. 2014.
[CrossRef]


[20] G. Wang, Z. Xu, F. Wen, K. P. Wong, "Traffic-constrained multiobjective planning of electric-vehicle charging stations," IEEE Transactions on Power Delivery, vol. 28, pp. 2363- 2372, Oct. 2013.
[CrossRef] [Web of Science Times Cited 289] [SCOPUS Times Cited 361]


[21] L. Yan, "Optimal Layout and Scale of Charging Stations for Electric Vehicles," in Proc. China International Conference on Electricity Distribution (CICED 2016), Xi'an, 2016, pp. 1-5.
[CrossRef] [SCOPUS Times Cited 7]


[22] S. A. MirHassani, R. Ebrazi, "A flexible reformulation of the refueling-station location problem," Transportation Science, vol. 47, no. 4, pp. 617-628, Sep 2012.
[CrossRef] [Web of Science Times Cited 181] [SCOPUS Times Cited 204]


[23] X. Xi, R. Sioshansi, V. Marano, "Simulation-optimization model for location of a public electric vehicle charging infrastructure," Transportation Research Part D: Transport and Environment, vol. 22, pp. 60-69, Jul. 2013.
[CrossRef] [Web of Science Times Cited 213] [SCOPUS Times Cited 263]


[24] I. Frade, A. Ribeiro, G. Gonçalves, A. P. Antunes, "Optimal location of charging stations for electric vehicles in a neighborhood in Lisbon, Portugal," Transportation Research Record, vol. 2252, pp. 91-98, Dec. 2011.
[CrossRef] [Web of Science Times Cited 280] [SCOPUS Times Cited 343]


[25] B. Oh, Y. Na, J. Yang, S. Park, J. Nang, J. Kim, "Genetic algorithm-based dynamic vehicle route search using car-to-car communication," Advances in Electrical and Computer Engineering, vol. 10, pp. 81- 86, Nov. 2014.
[CrossRef] [Full Text] [Web of Science Times Cited 16] [SCOPUS Times Cited 17]


[26] F. Zhan, "Three fastest shortest path algorithms on real road networks: Data structures and procedures," Journal of Geographic Information and Decision Analysis, vol. 1, no. 1, pp. 70-82, 1998.

[27] N. Touati-Moungla, V. Jost, "Combinatorial optimization for electric vehicles management," Journal of Energy & Power Engineering, vol. 6, no. 5, pp. 738-743, Jan. 2012.
[CrossRef]




References Weight

Web of Science® Citations for all references: 2,750 TCR
SCOPUS® Citations for all references: 3,606 TCR

Web of Science® Average Citations per reference: 98 ACR
SCOPUS® Average Citations per reference: 129 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-12-01 17:50 in 143 seconds.




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