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Optimal Location of Charging Stations for Electric Vehicles: A Theoretically-Sound Heuristic Model

Published: 07 June 2023 Publication History

Abstract

Due to the increasing awareness of the environmental dangerous effects of greenhouse gases emitted by fossil fuels, electricity is becoming a valid alternative as power source. Therefore, the amount of electric vehicles (EVs) in cities is gradually increasing. However, EVs suffer from driving range limitations compared to the traditional fossil-fuel-based vehicles. Users may need to charge their vehicle away from home and find a sufficient and convenient availability of public charging stations. In this so-delineated scenario, this paper proposes a theoretically-sound heuristic approach.

References

[1]
L. Adacher. 2018. Heuristics for Electric Vehicle Charging Station Allocation Problem. In 2018 5th International Conference on Mathematics and Computers in Sciences and Industry (MCSI). IEEE, 72--76.
[2]
Ladjel Bellatreche, Alfredo Cuzzocrea, and Soumia Benkrid. 2010. F&A: A Methodology for Effectively and Efficiently Designing Parallel Relational Data Warehouses on Heterogenous Database Clusters. In DAWAK 2010, Bilbao, Spain, August/September 2010. Proceedings. 89--104.
[3]
R. Bi, J. Xiao, D. Pelzer, D. Ciechanowicz, D. Eckhoff, and A. C. Knoll. 2017. A simulation-based heuristic for city-scale electric vehicle charging station placement. In 20th IEEE International Conference on Intelligent Transportation Systems, ITSC 2017, Yokohama, Japan, October 16--19, 2017. IEEE, 1--7.
[4]
J. Cavadas, G. H. de A. Correia, and J. Gouveia. 2015. A MIP model for locating slow-charging stations for electric vehicles in urban areas accounting for driver tours. Transportation Research Part E: Logistics and Transportation Review 75 (2015), 188--201.
[5]
Alfredo Cuzzocrea. 2013. Analytics over Big Data: Exploring the Convergence of DataWarehousing, OLAP and Data-Intensive Cloud Infrastructures. In COMPSAC 2013, Kyoto, Japan, July 22--26, 2013. IEEE Computer Society, 481--483.
[6]
G. Gatica, G. Ahumada, J. Escobar, and R. Linfati. 2018. Efficient Heuristic Algorithms for Location of Charging Stations in Electric Vehicle Routing Problems. Studies in Informatics and Control 27 (2018), 73--82.
[7]
F. He, Y. Yin, and J. Zhou. 2015. Deploying public charging stations for electric vehicles on urban road networks. Transportation Research Part C: Emerging Technologies 60 (2015), 227--240.
[8]
J. He, H. Yang, T.Q. Tang, and H.J. Huang. 2018. An optimal charging station location model with the consideration of electric vehicle's driving range. Transportation Research Part C: Emerging Technologies 86 (2018), 641--654.
[9]
M. Hosseini, S.A. MirHassani, and F. Hooshmand. 2017. Deviation-flow refueling location problem with capacitated facilities: Model and algorithm. Transportation Research Part D: Transport and Environment 54 (2017), 269--281.
[10]
M. Kuby and S. Lim. 2005. The flow-refueling location problem for alternative-fuel vehicles. Socio-Economic Planning Sciences 39, 2 (2005), 125--145.
[11]
Kuan-Ching Li, Hai Jiang, Laurence T. Yang, and Alfredo Cuzzocrea (Eds.). 2015. Big Data - Algorithms, Analytics, and Applications. Chapman and Hall/CRC.
[12]
Z. Liu, F. Wen, and G. Ledwich. 2013. Optimal Planning of Electric-Vehicle Charging Stations in Distribution Systems. IEEE Transactions on Power Delivery 28, 1 (2013), 102--110.
[13]
M. Miralinaghi, B. Keskin, Y. Lou, and A. Roshandeh. 2017. Capacitated Refueling Station Location Problem with Traffic Deviations Over Multiple Time Periods. Networks and Spatial Economics 17 (2017), 129--151.
[14]
S. A. MirHassani and R. Ebrazi. 2013. A Flexible Reformulation of the Refueling Station Location Problem. Transportation Science 47, 4 (2013), 617--628.
[15]
N. Shahraki, H. Cai, M. Turkay, and M. Xu. 2015. Optimal locations of electric public charging stations using real world vehicle travel patterns. Transportation Research Part D: Transport and Environment 41 (2015), 165--176.
[16]
Joglas Souza, Carson K. Leung, and Alfredo Cuzzocrea. 2020. An Innovative Big Data Predictive Analytics Framework over Hybrid Big Data Sources with an Application for Disease Analytics. In AINA 2020, Caserta, Italy, 15--17 April. 669--680.
[17]
Y. Wang, J. Shi, R. Wang, Z. Liu, and L. Wang. 2018. Siting and sizing of fast charging stations in highway network with budget constraint. Applied Energy 228 (2018), 1255--1271.
[18]
Haijun Yu, Hongliang Dai, Guangdong Tian, Yinghao Xie, Benben Wu, Ying Zhu, Hongliang Li, and Han Wu. 2020. Big-Data-Based Power Battery Recycling for New Energy Vehicles: Information Sharing Platform and Intelligent Transportation Optimization. IEEE Access 8 (2020), 99605--99623.

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  • (2023)A Machine Learning Methodology for Optimal Big Data Processing in Advanced Smart City EnvironmentsComputational Science and Its Applications – ICCSA 202310.1007/978-3-031-36805-9_46(713-730)Online publication date: 3-Jul-2023

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cover image ACM Conferences
SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing
March 2023
1932 pages
ISBN:9781450395175
DOI:10.1145/3555776
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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Publication History

Published: 07 June 2023

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Author Tags

  1. network algorithms
  2. theory of computing
  3. heuristic algorithms

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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  • (2023)A Machine Learning Methodology for Optimal Big Data Processing in Advanced Smart City EnvironmentsComputational Science and Its Applications – ICCSA 202310.1007/978-3-031-36805-9_46(713-730)Online publication date: 3-Jul-2023

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