A novel deep-learning based surrogate modeling of stochastic electric vehicle traffic user equilibrium in low-carbon electricity–transportation nexus
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DOI: 10.1016/j.apenergy.2022.118961
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- Tian, Xuelin & An, Chunjiang & Chen, Zhikun, 2023. "The role of clean energy in achieving decarbonization of electricity generation, transportation, and heating sectors by 2050: A meta-analysis review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
- Liang, Zeyu & Qian, Tao & Korkali, Mert & Glatt, Ruben & Hu, Qinran, 2024. "A Vehicle-to-Grid planning framework incorporating electric vehicle user equilibrium and distribution network flexibility enhancement," Applied Energy, Elsevier, vol. 376(PA).
- Menghwar, Mohan & Yan, Jie & Chi, Yongning & Asim Amin, M. & Liu, Yongqian, 2024. "A market-based real-time algorithm for congestion alleviation incorporating EV demand response in active distribution networks," Applied Energy, Elsevier, vol. 356(C).
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Keywords
Deep belief network; Electric vehicle; Edge-conditioned convolutional network; Transportation electrification; Traffic assignment problem; Traffic user equilibrium;All these keywords.
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