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Long-haul truck charging planning problem considering time flexibility and energy flexibility

Author

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  • Wan, Yuchun
  • He, Zhenggang
  • Gao, Yufan
  • Xue, Yujia

Abstract

The study explores opportunity charging as a solution for extending electric truck range during routine stops. It proposes a mixed-integer optimization model that combines opportunity charging with truck charging trip planning to optimize charging time and energy. The model examines variability in charging strategy and integrates potential driver choices and behaviors, including hub-charging and en-route charging options. An improved heuristic method is proposed, and the model's effectiveness is verified through numerical experiments. We present the Improved Dung Beetle Optimization (IDBO) algorithm based on the sine-cosine transformation process to solve the model. The proposed IDBO algorithm has the best optimization capability compared to typical genetic algorithms and traditional Dung Beetle Optimization (DBO), and the resulting total cost value was the lowest in all three cases used for the calculation.

Suggested Citation

  • Wan, Yuchun & He, Zhenggang & Gao, Yufan & Xue, Yujia, 2024. "Long-haul truck charging planning problem considering time flexibility and energy flexibility," Energy, Elsevier, vol. 306(C).
    • Handle: RePEc:eee:energy:v:306:y:2024:i:c:s0360544224021352
    DOI: 10.1016/j.energy.2024.132361
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    References listed on IDEAS

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