Open AccessBounded rational real‐time charging pricing strategy under the traffic‐grid coupling network
Author(s) -
Wang Chudi,
Ma Shaohua,
Cai Zhiyuan,
Yan Ning,
Wang Qiwei
Publication year - 2022
Publication title -
iet electrical systems in transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 26
eISSN - 2042-9746
pISSN - 2042-9738
DOI - 10.1049/els2.12050
Subject(s) - bounded rationality , bounded function , stackelberg competition , mathematical optimization , computer science , grid , game theory , economics , mathematics , mathematical economics , artificial intelligence , mathematical analysis , geometry
This study proposes a bounded rational charging guidance strategy based on mental account theory, which guides users to charge in an orderly manner by formulating real‐time charging prices. Firstly, an orderly guidance framework for fast‐charging EVs under the traffic‐grid coupling network is constructed, and the influencing factors of various dimensions when users make charging decisions are analysed. Secondly, considering the bounded rational behaviour of users when making charging decisions, a multifactor bounded rational charging model for EV users based on mental account theory is proposed so as to obtain different charging costs for users when selecting charging stations. On this basis, a real‐time charging price strategy based on the Stackelberg game model is constructed, with the goal of maximising the economic benefits of charging station operators while reducing the charging cost of EV users as much as possible. Finally, the particle swarm optimisation algorithm is used to solve the game model so as to solve the real‐time charging price under various constraints. The simulation of an example verifies the rationality of the proposed real‐time charging price formulation method and the superiority of the bounded rational charging guidance strategy.