A deep reinforcement learning-based charging scheduling approach with augmented Lagrangian for electric vehicles
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DOI: 10.1016/j.apenergy.2024.124706
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- Dorokhova, Marina & Martinson, Yann & Ballif, Christophe & Wyrsch, Nicolas, 2021. "Deep reinforcement learning control of electric vehicle charging in the presence of photovoltaic generation," Applied Energy, Elsevier, vol. 301(C).
- Tuchnitz, Felix & Ebell, Niklas & Schlund, Jonas & Pruckner, Marco, 2021. "Development and Evaluation of a Smart Charging Strategy for an Electric Vehicle Fleet Based on Reinforcement Learning," Applied Energy, Elsevier, vol. 285(C).
- Park, Keonwoo & Moon, Ilkyeong, 2022. "Multi-agent deep reinforcement learning approach for EV charging scheduling in a smart grid," Applied Energy, Elsevier, vol. 328(C).
- Zhao, Zhonghao & Lee, Carman K.M. & Ren, Jingzheng, 2024. "A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile," Applied Energy, Elsevier, vol. 355(C).
- Kreft, Markus & Brudermueller, Tobias & Fleisch, Elgar & Staake, Thorsten, 2024. "Predictability of electric vehicle charging: Explaining extensive user behavior-specific heterogeneity," Applied Energy, Elsevier, vol. 370(C).
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Keywords
Safe reinforcement learning; Electric vehicle; Constrained Markov decision process;All these keywords.
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