LAPSE:2023.11931
Published Article
LAPSE:2023.11931
An Approach for Pricing of Charging Service Fees in an Electric Vehicle Public Charging Station Based on Prospect Theory
Yan Bao, Fangyu Chang, Jinkai Shi, Pengcheng Yin, Weige Zhang, David Wenzhong Gao
February 28, 2023
Abstract
Within the context of sustainable development and a low-carbon economy, electric vehicles (EVs) are regarded as a promising alternative to engine vehicles. Since the increase of charging EVs brings new challenges to charging stations and distribution utility in terms of economy and reliability, EV charging should be coordinated to form a friendly and proper load. This paper proposes a novel approach for pricing of charging service fees in a public charging station based on prospect theory. This behavioral economics-based pricing mechanism will guide EV users to coordinated charging spontaneously. By introducing prospect theory, a model that reflects the EV owner’s response to price is established first, considering the price factor and the state-of-charge (SOC) of batteries. Meanwhile, the quantitative relationship between the utility value and the charging price or SOC is analyzed in detail. The EV owner’s response mechanism is used in modeling the charging load after pricing optimization. Accordingly, by using the particle swarm optimization algorithm, pricing optimization is performed to achieve multiple objectives such as minimizing the peak-to-valley ratio and electricity costs of the charging station. Through case studies, the determined time-of-use charging prices by pricing optimization is validated to be effective in coordinating EV users’ behavior, and benefiting both the station operator and power systems.
Keywords
charging service fee, electric vehicle, pricing, prospect theory, public charging station
Suggested Citation
Bao Y, Chang F, Shi J, Yin P, Zhang W, Gao DW. An Approach for Pricing of Charging Service Fees in an Electric Vehicle Public Charging Station Based on Prospect Theory. (2023). LAPSE:2023.11931
Author Affiliations
Bao Y: National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, Beijing 100044, China
Chang F: China Railway Engineering Design and Consulting Group Co., Ltd., Beijing 100055, China
Shi J: National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, Beijing 100044, China
Yin P: National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, Beijing 100044, China
Zhang W: National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, Beijing 100044, China
Gao DW: Department of Electrical and Computer Engineering, University of Denver, Denver, CO 80210, USA
Journal Name
Energies
Volume
15
Issue
14
First Page
5308
Year
2022
Publication Date
2022-07-21
ISSN
1996-1073
Version Comments
Original Submission
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PII: en15145308, Publication Type: Journal Article
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LAPSE:2023.11931
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https://doi.org/10.3390/en15145308
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