Bounded rational real‐time charging pricing strategy under the traffic‐grid coupling network

Abstract

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.

EV-Station-Grid Coordination Optimization Strategy Considering Psychological Preferences

“…When users make charging decisions, each attribute has a different proportion of influence on charging behavior. However, most of current decision-making models implicitly assume that the contribution of each dimension attribute to decision is the same [36,37] and do not consider the different impacts of each attribute on the decision results, so accurate decision results cannot be obtained. However, groups have the ability to learn and evolve.…”