Cost analysis of individual EV charging in different community networks

Fan Yi, Furong Li, Zechun Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The integration of electric vehicles (EVs) in the community network is gaining increasing attention nowadays. This paper proposes a new analytical methodology to calculate the energy costs of an individual EV in different community networks. Firstly, four representative EV charging demand (short journey vehicles, commuting vehicles, taxis, long journey vehicles) are classified statistically, according to their charging time, charging power, charging location and charging duration. It is a cost-effective methodology to provide feasible solutions through rational deductions, without the requirement for excessive data of charging activities. Thereafter, six scenarios in terms of different charging/discharging strategies, types of renewables and charging locations are proposed, to assess the different energy costs of EV charging behaviors. Further, the genetic algorithm (GA) is utilized in the optimal charging scenarios to calculate the most cost saving charging/discharging sequence and maximize the capture of renewables. The demonstration shows that the proposed analytical method reflects the characteristics of individual EV storage profiles and energy costs in dissimilar residential and commercial community networks. It also illustrated that the optimal charging strategy can reduce up to 96% energy cost for the electricity user.

Original languageEnglish
Title of host publication2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017
PublisherIEEE
ISBN (Electronic)9781538628942
DOIs
Publication statusPublished - 23 Oct 2017
Event2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017 - Harbin, China
Duration: 7 Aug 201710 Aug 2017

Conference

Conference2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017
CountryChina
CityHarbin
Period7/08/1710/08/17

Fingerprint

electric vehicle
Electric vehicles
costs
community
energy
Costs
scenario
deduction
methodology
electricity
Demonstrations
Electricity
Genetic algorithms
demand

Keywords

  • Demand-side management
  • Optimization
  • Plug-in electric vehicles

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology
  • Transportation

Cite this

Yi, F., Li, F., & Hu, Z. (2017). Cost analysis of individual EV charging in different community networks. In 2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017 [8080847] IEEE. https://doi.org/10.1109/ITEC-AP.2017.8080847

Cost analysis of individual EV charging in different community networks. / Yi, Fan; Li, Furong; Hu, Zechun.

2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017. IEEE, 2017. 8080847.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yi, F, Li, F & Hu, Z 2017, Cost analysis of individual EV charging in different community networks. in 2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017., 8080847, IEEE, 2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017, Harbin, China, 7/08/17. https://doi.org/10.1109/ITEC-AP.2017.8080847
Yi F, Li F, Hu Z. Cost analysis of individual EV charging in different community networks. In 2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017. IEEE. 2017. 8080847 https://doi.org/10.1109/ITEC-AP.2017.8080847
Yi, Fan ; Li, Furong ; Hu, Zechun. / Cost analysis of individual EV charging in different community networks. 2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2017. IEEE, 2017.
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