Battery charging of electric vehicles (EVs) needs to be properly coordinated by electricity producers to maintain network reliability. In this paper, we propose a robust approach to model the interaction between a large fleet of EV users and utilities in a long-term generation expansion planning problem. In doing so, we employ a robust multi-period adjustable generation expansion planning problem, called R-ETEM, in which demand responses of EV users are uncertain. Then, we employ a linear-quadratic game to simulate the average charging behavior of EV users. The two models are coupled through a dynamic price signal broadcasted by the utility. Mean _eld game theory is used to solve the linear-quadratic game model. Finally, we develop a new coupling algorithm between R-ETEM and the linear-quadratic game with the purpose of adjusting in R-ETEM the uncertainty level of EV demand responses. The performance of our approach is evaluated on a realistic case study that represents the energy system of the Swiss “Arc Lemanique” region. Results show that a robust behaviorally consistent generation expansion plan can potentially reduce the total actual cost of the system by 6.2% compared to a behaviorally inconsistent expansion plan.
Department of Decision Sciences, HEC Montreal, Montreal, Quebec, H3T 2A7, Canada. July 2021.
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