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Internet of smart charging points with photovoltaic Integration: A high-efficiency scheme enabling optimal dispatching between electric vehicles and power grids

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Listed:
  • Shang, Yitong
  • Liu, Man
  • Shao, Ziyun
  • Jian, Linni

Abstract

Plug-in electric vehicles (PEVs) and renewable energy sources (RESs) can relief the stress on air pollution. Particularly, using RES for PEV energy requirement can integrate more RESs on the grid. In this paper, a vehicle-to-grid (V2G) scheme concerning on RES and edge computing, i.e. the internet of smart charging points with photovoltaics integration, is presented. Within the architecture of the scheme, each charging point equips computing and storage units, so as to store PEV sensitive information locally and conduct “burn after scheduling”. Besides, this architecture can transform the traditional large-scale V2G problem into several sub-problems, which are small enough to optimize. Based on the architecture of the scheme, an associated high-efficiency algorithm is designed. Six typical scenarios of PEV charging are elaborated and two indexes are presented to facilitate 1) the self-consumption of photovoltaics energy by PEV charging and 2) the peak-shaving and valley-filling of net load. Additionally, voltage regulation and real-time control are applied to ensure the security of the distribution grid and mitigate the uncertain conditions. Finally, compared with uncoordinated charging, the short-time scale simulation realizes the peak-shaving and valley-filling by 17.54% and 12.42%, respectively; and the amount of self-consumption of photovoltaics energy increases by 258.74%. Furthermore, the long-time scale simulations also present a satisfying performance for the grid energy saving and the load factor. Particularly, the proposed scheme offers high computational efficiency compared with different architecture and algorithm, and the execution time for scheduling one PEV at one-time interval shows a microsecond basis.

Suggested Citation

  • Shang, Yitong & Liu, Man & Shao, Ziyun & Jian, Linni, 2020. "Internet of smart charging points with photovoltaic Integration: A high-efficiency scheme enabling optimal dispatching between electric vehicles and power grids," Applied Energy, Elsevier, vol. 278(C).
    • Handle: RePEc:eee:appene:v:278:y:2020:i:c:s0306261920311417
    DOI: 10.1016/j.apenergy.2020.115640
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    Cited by:

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    2. Sun, Chuyu & Zhao, Xiaoli & Qi, Binbin & Xiao, Weihao & Zhang, Hongjun, 2022. "Economic and environmental analysis of coupled PV-energy storage-charging station considering location and scale," Applied Energy, Elsevier, vol. 328(C).
    3. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).
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    5. Syed Taha Taqvi & Ali Almansoori & Azadeh Maroufmashat & Ali Elkamel, 2022. "Utilizing Rooftop Renewable Energy Potential for Electric Vehicle Charging Infrastructure Using Multi-Energy Hub Approach," Energies, MDPI, vol. 15(24), pages 1-21, December.
    6. Yu, Hang & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jia, Youwei & Jian, Linni, 2022. "Electric vehicles integration and vehicle-to-grid operation in active distribution grids: A comprehensive review on power architectures, grid connection standards and typical applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    7. Prince Waqas Khan & Yung-Cheol Byun, 2021. "Blockchain-Based Peer-to-Peer Energy Trading and Charging Payment System for Electric Vehicles," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    8. Shang, Yitong & Yu, Hang & Niu, Songyan & Shao, Ziyun & Jian, Linni, 2021. "Cyber-physical co-modeling and optimal energy dispatching within internet of smart charging points for vehicle-to-grid operation," Applied Energy, Elsevier, vol. 303(C).
    9. Akansha Jain & Masoud Karimi-Ghartemani, 2022. "Mitigating Adverse Impacts of Increased Electric Vehicle Charging on Distribution Transformers," Energies, MDPI, vol. 15(23), pages 1-26, November.

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