V2G Capability Evaluation Based on Willingness-Decision Framework Under Multi-Factor Constraints

In the process of rapid popularization of electric vehicles (EV), vehicle to grid (V2G) technology has gradually become an important means to promote the consumption of renewable energy. Currently, the evaluation methods for V2G capability still face challenges such as incomplete coverage of evaluation objects, difficulties in matching stable discharge states with unit discharge timings, and the inability to comprehensively consider multiple influencing factors. Based on these issues, this study proposes a stable V2G capability evaluation method that is based on maximum discharge potential assessment, which incorporates user decision under multiple influencing factors. The results show that the user decisions to participate is most affected by battery degradation. Under the normal temperature (0-40°C), the V2G capability of urban EV conforms to the user’s travel habits, while under the low temperature environment (<0°C), the battery degradation is serious, user practical decisions are reduced, and the V2G capability is reduced by 49.3%.

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Publication Details

Published
2025-07-04
DOI
https://doi.org/10.1109/icpet66029.2025.11160500
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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V2G Capability Evaluation Based on Willingness-Decision Framework Under Multi-Factor Constraints

Min Guo, Zhuo Hu, Qixin Yao, Yuting Zheng et al.
Advanced MIMO Systems Optimization
article

V2G Capability Evaluation Based on Willingness-Decision Framework Under Multi-Factor Constraints

Min Guo, Zhuo Hu, Qixin Yao, Yuting Zheng, Xu Yang, Yankun Zhu
article en

Abstract

In the process of rapid popularization of electric vehicles (EV), vehicle to grid (V2G) technology has gradually become an important means to promote the consumption of renewable energy. Currently, the evaluation methods for V2G capability still face challenges such as incomplete coverage of evaluation objects, difficulties in matching stable discharge states with unit discharge timings, and the inability to comprehensively consider multiple influencing factors. Based on these issues, this study proposes a stable V2G capability evaluation method that is based on maximum discharge potential assessment, which incorporates user decision under multiple influencing factors. The results show that the user decisions to participate is most affected by battery degradation. Under the normal temperature (0-40°C), the V2G capability of urban EV conforms to the user’s travel habits, while under the low temperature environment (<0°C), the battery degradation is serious, user practical decisions are reduced, and the V2G capability is reduced by 49.3%.

State Grid Corporation of China (China) (CN), Wuhan University of Technology (CN)
Openalex Percentile: Top 76%
Advanced MIMO Systems Optimization
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