An Electric Taxi Charging Station Planning Scheme Based on an Improved Destination Choice Method

Ruifeng Shi, Jiahua Liu, Zhenhong Liao, Li Niu, Eke Ibrahim and Fang Fu
Additional contact information
Ruifeng Shi: School of Control & Computer Engineering, North China Electric Power University, Beijing 102206, China
Jiahua Liu: School of Control & Computer Engineering, North China Electric Power University, Beijing 102206, China
Zhenhong Liao: Guangdong Power Grid Co., Ltd. Zhanjiang Power Supply Bureau, Zhanjiang 524002, China
Li Niu: School of Information Resource Management, Renmin University of China, Beijing 100872, China
Eke Ibrahim: Department of Electrical and Electronics Engineering, Kırıkkale University, Kirikkale 71451, Turkey
Fang Fu: School of Economics & Management, China University of Petroleum, Qingdao 266580, China

Energies, 2019, vol. 12, issue 19, 1-21

Abstract: The environmental crisis has prompted the development of electric vehicles as a green and environmentally friendly mode of travel. Since a reasonable layout of electric vehicle (EV) charging stations is the prerequisite for developing the EV industry, obtaining an optimal and efficient EV charging station planning scheme is a key issue. Although the Chinese government has carried out a plan to build EV charging piles in residential and working places, it cannot properly fulfill the task of matching the charging needs for public transportation vehicles such as electric taxis (ETs). How to evaluate the performance of fast charging stations (FCSs) and how to help find the optimal ET charging station planning scheme are new challenges. In this paper, an improved destination selection model is proposed to simulate the ET operation system and to help find the optimal ET charging station size with statistical analysis based on the charging need prediction. A numerical case study shows that the proposed method can address ET charging behavior well and can help to statistically determine the size of each ET charging station, which should satisfy the constraints on the preset proportion of the ET charging service requests.

Keywords: electric taxis; destination selection model; statistical analysis; charging station deployment plan (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/19/3781/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/19/3781/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:19:p:3781-:d:273775

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().