As electric vehicle adoption accelerates globally, battery swapping stations represent an alternative to traditional plug-in charging infrastructure. Unlike conventional charging, swapping allows drivers to exchange depleted batteries for fully charged ones in minutes. However, with multiple competing operators entering this market, questions arise about how stations should price services and manage charging operations to remain profitable.
Researchers addressed this challenge through a two-stage game-theoretic framework. In the first stage, battery swapping stations independently set swapping prices in the day-ahead market. In the second stage, they optimize their battery charging schedules in the real-time market based on actual demand patterns. The model mathematically guarantees the existence and uniqueness of a Subgame Perfect Nash Equilibrium—a theoretical condition ensuring all stations arrive at optimal strategies simultaneously.
The research is particularly relevant for markets with aggregators coordinating multiple competing stations, a structure already emerging in China and other regions. By proving the equilibrium is unique, the authors provide theoretical justification that stations following their recommended strategy cannot improve profits by deviating unilaterally.
Testing the framework on a 12-station system using real-world data from Xi'an revealed substantial benefits. Individual station profitability increased by at least 18.1% compared to baseline strategies. Additionally, the optimal charging approach naturally created peak-shaving effects on the power grid—charging concentrated during off-peak hours when electricity is cheaper and less strained.
The researchers also proposed a demand prediction error handling method to protect stations against unexpected fluctuations in swapping requests. This practical addition addresses real-world uncertainty in customer behavior. As battery swapping networks scale, such optimization models could become essential decision-support tools for operators managing pricing competitively while contributing to broader grid stability objectives.
