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September 10, 2025EnergiesOpen Access

Multi-User Satisfaction-Driven Bi-Level Optimization of Electric Vehicle Charging Strategies

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Authors

BCB. R. ChenJXJiangjiao XuDLDongdong Li

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Overview

This framework demonstrates cost reduction of 32.6% in electric vehicle charging, highlighting user-specific satisfaction and dynamic pricing strategies.

Key Points

  • The proposed optimization framework reduced costs by 32.6% among various user types, improving overall efficiency.
  • Analysis shows statistically significant improvements in expenditure optimization, with a p-value less than 0.01.
  • A bi-level optimization architecture utilizes deep reinforcement learning to address user-specific demand in charging strategies.
  • Interpretability analysis confirms the framework's effectiveness in aligning attention mechanisms with user demand patterns.

Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/68c1b18554b1d3bfb60e83a4https://doi.org/10.3390/en18154097
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