Dynamic pricing for integrated energy-traffic systems from a cyber-physical-human perspective. (February 2021)

• Record Type: Journal Article
• Authors: Yang, Tianyu; Guo, Qinglai; Xu, Luo; Sun, Hongbin
• Is Part Of: Renewable & sustainable energy reviews. Volume 136(2021)
• Publication Date: 2021-02
• Subjects: Electric vehicles -- Ride-hailing services -- Cyber-physical-human system; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2020.110419
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: This paper solves the vehicle assignment problem of an operating entity with dispatchable vehicles (e.g., an urban Integrated Energy-Traffic System (IETS) coordinator or an e-hailing company) in the context of energy-traffic coordinated modeling and analysis. Current research on electric vehicle (EV) scheduling and optimization has broadly assumed that human beings are rational decision-makers and obey the scheduling plan. In contrast, we proposed a user-centric dynamic pricing scheme that improves the system performance by incentivizing human participants to follow the expected behavioral patterns from a Cyber-Physical-Human System (CPHS) perspective. The interdisciplinary fields of power systems, traffic systems, and human decision-making were used to study the interactions in the CPHS. The proposed incentive scheme was applied to the urban IETS scenarios based on real-world Global Positioning System (GPS) data of EV taxis, and the results showed that it effectively optimized the integrated system. Highlights: Dynamic pricing scheme proposed for dispatching electric vehicles in an urban area. Proposed scheme combines energy and traffic systems. Unlike current research, human users are not assumed to be rational. Proposed scheme incentivizes users to follow expected behavioral patterns. Proposed scheme applied to real-world EV taxi data for validation.