Interactive optimization of electric vehicles and park integrated energy system driven by low carbon: An incentive mechanism based on Stackelberg game

Shaobo Shi, Yuehui Ji, Lewei Zhu, Junjie Liu, Xiang Gao, Hao Chen and Qiang Gao

Energy, 2025, vol. 318, issue C

Abstract: The rapid growth of electric vehicles has reduced the operational stability of the park’s integrated energy system. To address this, this paper proposes a low-carbon, economic dispatch method for the park’s energy system. The method incentivizes electric vehicles to participate in vehicle-grid interaction. First, an electric vehicle charging and discharging incentive model is designed, accounting for battery degradation. The model encourages users to charge during excess electricity and discharge during peak demand. This helps balance the park’s electricity supply and demand. Next, a stepped carbon trading model is introduced. It allows electric vehicles to gain extra benefits by participating in carbon trading. Finally, based on Stackelberg game theory, a leader–follower model is constructed. The park operator act as the leader. Distributed energy supplier, electric vehicle load aggregator, and conventional load aggregators are the followers. The study found that the proposed electric vehicle charging and discharging incentive model increases electric vehicle users’ willingness to feed electricity back to the grid by 48.33%, boosted their maximum consumer surplus by 57.2%, and reduced the total daily operating costs of distributed energy providers by 1.5%.

Keywords: Park integrated energy system; Vehicle to grid; Dynamic incentive; Carbon trading; Stackelberg game (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:318:y:2025:i:c:s0360544225004414

DOI: 10.1016/j.energy.2025.134799

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