Evolutionary Dynamics and Policy Coordination in the Vehicle–Grid Interaction Market: A Tripartite Evolutionary Game Analysis

Qin Shao, Ying Lyu and Jian Cao ()
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Qin Shao: College of Management, Zhejiang University of Technology, Hangzhou 310023, China
Ying Lyu: College of Management, Zhejiang University of Technology, Hangzhou 310023, China
Jian Cao: College of Management, Zhejiang University of Technology, Hangzhou 310023, China

Mathematics, 2025, vol. 13, issue 15, 1-27

Abstract: This study introduces a novel tripartite evolutionary game model to analyze the strategic interactions among electric vehicle (EV) aggregators, local governments, and EV users in vehicle–grid interaction (VGI) markets. The core novelty lies in capturing bounded rationality and dynamic decision-making across the three stakeholders, revealing how policy incentives and market mechanisms drive the transition from disordered charging to bidirectional VGI. Key findings include the following: (1) The system exhibits five stable equilibrium points, corresponding to three distinct developmental phases of the VGI market: disordered charging (V0G), unidirectional VGI (V1G), and bidirectional VGI (V2G). (2) Peak–valley price differences are the primary driver for transitioning from V0G to V1G. (3) EV aggregators’ willingness to adopt V2G is influenced by upgrade costs, while local governments’ subsidy strategies depend on peak-shaving benefits and regulatory costs. (4) Increasing the subsidy differential between V1G and V2G accelerates market evolution toward V2G. The framework offers actionable policy insights for sustainable VGI development, while advancing evolutionary game theory applications in energy systems.

Keywords: vehicle–grid interaction; EV aggregators; government behavior; tripartite evolutionary game; numerical simulation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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