Optimal DC Fast Charging Placing And Sizing In Iran Capital (Tehran)

Document Type : Research Article

Authors

Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran

Abstract

DC fast charging (DCFC) and optimal placing of them is a fundamental factor for the popularization of electric vehicles (EVs). This paper proposes an approach to optimize place and size of charging stations based on genetic algorithm (GA). Target of this method is minimizing cost of conversion of gas stations to charging stations. Another considered issue is minimizing EVs losses to find nearest station to recharge batteries. The introduced model forms a mixed-integer non-linear problem and is solved by binary GA and is adopted for finding the optimal place and size of charging stations in Iran capital (Tehran). This practical study proves that the proposed model and method are feasible. Existing gas stations in Tehran are selected as candidate to be converted as DC fast charging. EVs has been outspread throughout of city based on traffic and trips in each municipal districts. The model developed here can be generalized to data set for any region or city and can be used for governmental decision for constructing charging station infrastructure.

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Main Subjects

References

[1] J. Saarenpää, M. Kolehmainen, H. Niska, Geodemographic analysis and estimation of early plug-in hybrid electric vehicle adoption, Applied Energy, 107 (2013) 456-464.
[2] I.R.o.I.M.o. Energy, Iran energy balance 1392, (Aug 2015).
[3] N.I.O.P.D.C. (NIOPDC), consumption of petrolium products statistics – 1393, (Nov 2015).
[4] H. Quebec, Electric Vehicle Charging Stations Technical Installation Guide, in, no. August, 2015.
[5] C. Botsford, A. Szczepanek, Fast charging vs. slow charging: Pros and cons for the new age of electric vehicles, in: International Battery Hybrid Fuel Cell Electric Vehicle Symposium, 2009.
[6] C. Chen, G. Hua, A new model for optimal deployment of electric vehicle charging and battery swapping stations, International Journal of Control & Automation, 8(5) (2014).
[7] S. Ge, L. Feng, H. Liu, The planning of electric vehicle charging station based on grid partition method, in: Electrical and Control Engineering (ICECE), 2011 International Conference on, IEEE, 2011, pp. 2726-2730.
[8] M. Jin, R. Shi, N. Zhang, Y. Li, Study on multi-level layout planning of electric vehicle charging stations based on an improved genetic algorithm, International Journal of Smart Grid and Clean Energy, 2(2) (2013) 277-282.
[9] H. Xu, S. Miao, C. Zhang, D. Shi, Optimal placement of charging infrastructures for large-scale integration of pure electric vehicles into grid, International Journal of Electrical Power & Energy Systems, 53 (2013) 159-165.
[10] Z. Liu, F. Wen, G. Ledwich, Optimal planning of electric-vehicle charging stations in distribution systems, IEEE Transactions on Power Delivery, 28(1) (2013) 102-110.
[11] C. Dharmakeerthi, N. Mithulananthan, T. Saha, A comprehensive planning framework for electric vehicle charging infrastructure deployment in the power grid with enhanced voltage stability, International Transactions on Electrical Energy Systems, 25(6) (2015) 1022-1040.
[12] Z.-f. Liu, W. Zhang, X. Ji, K. Li, Optimal planning of charging station for electric vehicle based on particle swarm optimization, in: Innovative Smart Grid Technologies-Asia (ISGT Asia), 2012 IEEE, IEEE, 2012, pp. 1-5.
[13] S. Mehar, S.M. Senouci, An optimization location scheme for electric charging stations, IEEE SaCoNet, (2013) 1-5.
[14] P. Sadeghi-Barzani, A. Rajabi-Ghahnavieh, H. Kazemi-Karegar, Optimal fast charging station placing and sizing, Applied Energy, 125 (2014) 289-299.
[15] S. center, final results for Tehran (22regions), (2007).
[16] G. Maps, Tehran Accessed Nov 2, (2015 ).
[17] T.c.t.a.t. co, selected data and information of urban transportation in Tehran – 1392, (2013).
[18] N.I.O.p.d.c.N.-T. region, address and phone of gas stations in Tehran based on region, (Nov 2015).
[19] C. Cities, Plug-In Electric Vehicle Handbook for Public Charging Station Hosts, US Department of Energy Publication No. DOE/GO-102012-3275, (2012).
AUT Journal of Electrical Engineering
Volume 50, Issue 2
December 2018
Pages 149-156

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