Bowen Du
ABSTRACT
Cars of the future have been predicted as shared and electric. There has been a rapid growth in electric vehicle (EV) sharing services worldwide in recent years. For EV-sharing platforms to excel, it is essential for them to offer private charging infrastructure for exclusive use that meets the charging demand of their clients. Particularly, they need to plan not only the places to build charging stations, but also the amounts of chargers per station, to maximally satisfy the requirements on global charging coverage and local charging demand. Existing research efforts are either inapplicable for their different problem formulations or are at a coarse granularity. In this paper, we formulate the \underlineE lectric \underlineV ehicle \underlineC harger \underlineP lanning (EVCP) problem especially for EV-sharing. We prove that the \shortpro problem is NP-hard, and design an approximation algorithm to solve the problem with a theoretical bound of $1-\frac1 e $. We also devise some optimization techniques to speed up the solution. Extensive experiments on real-world datasets validate the effectiveness and the efficiency of our proposed solutions.
- Charles Botsford and Adam Szczepanek . 2009. Fast Charging vs. Slow Charging: Pros and cons for the New Age of Electric Vehicles International Battery Hybrid Fuel Cell Electric Vehicle Symposium.Google Scholar
- T Donna Chen, Kara M Kockelman, William J Murray, and Moby Khan . 2013. The electric vehicle charging station location problem: a parking-based assignment method for Seattle. In Transportation Research Board 92nd Annual Meeting, Vol. Vol. 340. 13--1254.Google Scholar
- Reza Zanjirani Farahani and Masoud Hekmatfar . 2009. Facility location: concepts, models, algorithms and case studies. Springer.Google Scholar
- Inês Frade, Anabela Ribeiro, Gonccalo Gonccalves, and António Antunes . 2011. Optimal location of charging stations for electric vehicles in a neighborhood in Lisbon, Portugal. Transportation research record: journal of the transportation research board 2252 (2011), 91--98.Google ScholarCross Ref
- Yajing Gao and Yandong Guo . 2013. Optimal Planning of Charging Station for Phased Electric Vehicle. Energy & Power Engineering Vol. 05, 4 (2013), 1393--1397.Google ScholarCross Ref
- Fang He, Di Wu, Yafeng Yin, and Yongpei Guan . 2013. Optimal deployment of public charging stations for plug-in hybrid electric vehicles. Transportation Research Part B: Methodological Vol. 47 (2013), 87--101.Google ScholarCross Ref
- Dorit S Hochbaum . 1996. Approximation algorithms for NP-hard problems. PWS Publishing Company. Google ScholarDigital Library
- Long Jia, Zechun Hu, Yonghua Song, and Zhuowei Luo . 2012. Optimal siting and sizing of electric vehicle charging stations IEEE International Electric Vehicle Conference, IEVC 2012. IEEE, 1--6.Google Scholar
- Albert Y. S. Lam, Yiu-Wing Leung, and Xiaowen Chu . 2014. Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions. IEEE Transactions on Smart Grid Vol. 5, 6 (2014), 2846--2856.Google ScholarCross Ref
- Yanhua Li, Jun Luo, Chi-Yin Chow, Kam-Lam Chan, Ye Ding, and Fan Zhang . 2015. Growing the charging station network for electric vehicles with trajectory data analytics 31st IEEE International Conference on Data Engineering, ICDE 2015. 1376--1387.Google ScholarCross Ref
- Chen Liu, Ke Deng, Chaojie Li, Jianxin Li, Yanhua Li, and Jun Luo . 2016. The Optimal Distribution of Electric-Vehicle Chargers across a City 16th IEEE International Conference on Data Mining, ICDM 2016. 261--270.Google Scholar
- Zhipeng Liu, Fushuan Wen, and Gerard Ledwich . 2012 a. Optimal Planning of Electric-Vehicle Charging Stations in Distribution Systems. IEEE Transactions on Power Delivery Vol. 28, 1 (2012), 102--110.Google ScholarCross Ref
- Zi Fa Liu, Wei Zhang, Ji Xing, and Ke Li . 2012 b. Optimal Planning of charging station for electric vehicle based on particle swarm optimization. In IEEE Innovative Smart Grid Technologies-Asia, ISGT Asia 2012. 1--5.Google Scholar
- George L. Nemhauser, Laurence A. Wolsey, and Marshall L. Fisher . 1978. An analysis of approximations for maximizing submodular set functions - I. Mathematical Programming Vol. 14, 1 (1978), 265--294. Google ScholarDigital Library
- Morgan Stanley Blue Papers . 2016. Shared Mobility on the Road of the Future. https://goo.gl/onaZn1. (2016).Google Scholar
- Alexander Schrijver . 1998. Theory of linear and integer programming. John Wiley & Sons.Google Scholar
- Yongxin Tong, Yuqiang Chen, Zimu Zhou, Lei Chen, Jie Wang, Qiang Yang, Jieping Ye, and Weifeng Lv . 2017 a. The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, SIGKDD 2017. 1653--1662. Google ScholarDigital Library
- Yongxin Tong, Jieying She, Bolin Ding, Libin Wang, and Lei Chen . 2016. Online mobile Micro-Task Allocation in spatial crowdsourcing 32nd IEEE International Conference on Data Engineering, ICDE 2016. 49--60.Google Scholar
- Yongxin Tong, Libin Wang, Zimu Zhou, Lei Chen, Bowen Du, and Jieping Ye . 2018. Flexible Online Task Assignment in Real-Time Spatial Data Proceedings of the 37th ACM SIGMOD International Conference on Management of Data, SIGMOD 2018.Google Scholar
- Yongxin Tong, Libin Wang, Zimu Zhou, Bolin Ding, Lei Chen, Jieping Ye, and Ke Xu . 2017 b. Flexible Online Task Assignment in Real-Time Spatial Data. PVLDB Vol. 10, 11 (2017), 1334--1345. Google ScholarDigital Library
- Wikipedia . 2017. Autolib'. https://en.wikipedia.org/wiki/Autolib%27. (2017).Google Scholar
- James H Williams, Andrew DeBenedictis, Rebecca Ghanadan, Amber Mahone, Jack Moore, William R Morrow, Snuller Price, and Margaret S Torn . 2012. The technology path to deep greenhouse gas emissions cuts by 2050: the pivotal role of electricity. Science Vol. 335, 6064 (2012), 53--59.Google ScholarCross Ref
- Yanhai Xiong, Jiarui Gan, Bo An, Chunyan Miao, and Ana L. C. Bazzan . 2015. Optimal Electric Vehicle Charging Station Placement Proceedings of the 24th International Joint Conference on Artificial Intelligence, IJCAI 2015. 2662--2668. Google ScholarDigital Library
Index Terms
- Demand-Aware Charger Planning for Electric Vehicle Sharing
Recommendations
Genetic Algorithm for Optimal Charge Scheduling of Electric Vehicle Fleet
NISS '19: Proceedings of the 2nd International Conference on Networking, Information Systems & SecurityElectric Vehicles (EV) are gradually conquering more roads and replacing pollutant conventional vehicles. They seem to be used to store energy in clean and smart grids to mitigate greenhouse gas emissions and eliminate harmful peak loads. This paper ...
Charging Planning of Electric Vehicle Manager Based on Price Demand
WABD 2021: 2021 Workshop on Algorithm and Big DataThe charging technology of electric vehicles has always affected the development of electric vehicles. If you want to use electric vehicles to provide travel services like fuel cars, electric vehicle service providers must consider the charging problem ...
Optimal Policies for the Management of an Electric Vehicle Battery Swap Station
Optimizing operations at electric vehicle EV battery swap stations is internally motivated by the movement to make transportation cleaner and more efficient. An EV battery swap station allows EV owners to quickly exchange their depleted battery for a ...
Comments