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Dynamic programming-based optimisation of charging an electric vehicle fleet system represented by an aggregate battery model

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Cited by:

  1. Jin, Ruiyang & Zhou, Yuke & Lu, Chao & Song, Jie, 2022. "Deep reinforcement learning-based strategy for charging station participating in demand response," Applied Energy, Elsevier, vol. 328(C).
  2. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  3. Liu, Lu & Zhou, Kaile, 2022. "Electric vehicle charging scheduling considering urgent demand under different charging modes," Energy, Elsevier, vol. 249(C).
  4. Fanrong Kong & Jianhui Jiang & Zhigang Ding & Junjie Hu & Weian Guo & Lei Wang, 2017. "A Personalized Rolling Optimal Charging Schedule for Plug-In Hybrid Electric Vehicle Based on Statistical Energy Demand Analysis and Heuristic Algorithm," Energies, MDPI, vol. 10(9), pages 1-18, September.
  5. Tan, Ruipeng & Tang, Di & Lin, Boqiang, 2018. "Policy impact of new energy vehicles promotion on air quality in Chinese cities," Energy Policy, Elsevier, vol. 118(C), pages 33-40.
  6. Yu, Shiwei & Gao, Siwei & sun, Han, 2016. "A dynamic programming model for environmental investment decision-making in coal mining," Applied Energy, Elsevier, vol. 166(C), pages 273-281.
  7. Jaehyun Lee & Eunjung Lee & Jinho Kim, 2020. "Electric Vehicle Charging and Discharging Algorithm Based on Reinforcement Learning with Data-Driven Approach in Dynamic Pricing Scheme," Energies, MDPI, vol. 13(8), pages 1-18, April.
  8. Zongfei Wang & Patrick Jochem & Hasan Ümitcan Yilmaz & Lei Xu, 2022. "Integrating vehicle‐to‐grid technology into energy system models: Novel methods and their impact on greenhouse gas emissions," Journal of Industrial Ecology, Yale University, vol. 26(2), pages 392-405, April.
  9. Ju, Fei & Zhuang, Weichao & Wang, Liangmo & Zhang, Zhe, 2019. "Optimal sizing and adaptive energy management of a novel four-wheel-drive hybrid powertrain," Energy, Elsevier, vol. 187(C).
  10. Cesar Diaz-Londono & Luigi Colangelo & Fredy Ruiz & Diego Patino & Carlo Novara & Gianfranco Chicco, 2019. "Optimal Strategy to Exploit the Flexibility of an Electric Vehicle Charging Station," Energies, MDPI, vol. 12(20), pages 1-29, October.
  11. Jinquan, Guo & Hongwen, He & Jiankun, Peng & Nana, Zhou, 2019. "A novel MPC-based adaptive energy management strategy in plug-in hybrid electric vehicles," Energy, Elsevier, vol. 175(C), pages 378-392.
  12. Chung, Cheng-Ta & Hung, Yi-Hsuan, 2015. "Performance and energy management of a novel full hybrid electric powertrain system," Energy, Elsevier, vol. 89(C), pages 626-636.
  13. Škugor, Branimir & Deur, Joško, 2015. "A novel model of electric vehicle fleet aggregate battery for energy planning studies," Energy, Elsevier, vol. 92(P3), pages 444-455.
  14. Lin, Cheng & Zhao, Mingjie & Pan, Hong & Yi, Jiang, 2019. "Blending gear shift strategy design and comparison study for a battery electric city bus with AMT," Energy, Elsevier, vol. 185(C), pages 1-14.
  15. Schücking, Maximilian & Jochem, Patrick, 2021. "Two-stage stochastic program optimizing the cost of electric vehicles in commercial fleets," Applied Energy, Elsevier, vol. 293(C).
  16. Hu, Xiaosong & Zou, Yuan & Yang, Yalian, 2016. "Greener plug-in hybrid electric vehicles incorporating renewable energy and rapid system optimization," Energy, Elsevier, vol. 111(C), pages 971-980.
  17. Cauchi, Nathalie & Macek, Karel & Abate, Alessandro, 2017. "Model-based predictive maintenance in building automation systems with user discomfort," Energy, Elsevier, vol. 138(C), pages 306-315.
  18. Parinaz Aliasghari & Behnam Mohammadi-Ivatloo & Mehdi Abapour & Ali Ahmadian & Ali Elkamel, 2020. "Goal Programming Application for Contract Pricing of Electric Vehicle Aggregator in Join Day-Ahead Market," Energies, MDPI, vol. 13(7), pages 1-12, April.
  19. Yang Shen & Jiaming Zhou & Jinming Zhang & Fengyan Yi & Guofeng Wang & Chaofeng Pan & Wei Guo & Xing Shu, 2023. "Research on Energy Management of Hydrogen Fuel Cell Bus Based on Deep Reinforcement Learning Considering Velocity Control," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
  20. Chen, Syuan-Yi & Wu, Chien-Hsun & Hung, Yi-Hsuan & Chung, Cheng-Ta, 2018. "Optimal strategies of energy management integrated with transmission control for a hybrid electric vehicle using dynamic particle swarm optimization," Energy, Elsevier, vol. 160(C), pages 154-170.
  21. Morteza Nazari-Heris & Mehdi Abapour & Behnam Mohammadi-Ivatloo, 2022. "An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks," Sustainability, MDPI, vol. 14(23), pages 1-24, November.
  22. Rachana Vidhi & Prasanna Shrivastava & Abhishek Parikh, 2021. "Social and Technological Impact of Businesses Surrounding Electric Vehicles," Clean Technol., MDPI, vol. 3(1), pages 1-17, February.
  23. Liu, Teng & Wang, Bo & Yang, Chenglang, 2018. "Online Markov Chain-based energy management for a hybrid tracked vehicle with speedy Q-learning," Energy, Elsevier, vol. 160(C), pages 544-555.
  24. Andre Leippi & Markus Fleschutz & Michael D. Murphy, 2022. "A Review of EV Battery Utilization in Demand Response Considering Battery Degradation in Non-Residential Vehicle-to-Grid Scenarios," Energies, MDPI, vol. 15(9), pages 1-22, April.
  25. Schücking, Maximilian & Jochem, Patrick & Fichtner, Wolf & Wollersheim, Olaf & Stella, Kevin, 2017. "Charging strategies for economic operations of electric vehicles in commercial applications," MPRA Paper 91599, University Library of Munich, Germany.
  26. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.
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