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Internet of Energy Approach for Sustainable Use of Electric Vehicles as Energy Storage of Prosumer Buildings

Author

Listed:
  • Evgeny Nefedov

    (Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland)

  • Seppo Sierla

    (Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland)

  • Valeriy Vyatkin

    (Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland
    Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, 97187 Luleå, Sweden)

Abstract

Vehicle-to-building (V2B) technology permits bypassing the power grid in order to supply power to a building from electric vehicle (EV) batteries in the parking lot. This paper investigates the hypothesis stating that the increasing number of EVs on our roads can be also beneficial for making buildings sustainably greener on account of using V2B technology in conjunction with local photovoltaic (PV) generation. It is assumed that there is no local battery storage other than EVs and that the EV batteries are fully available for driving, so that the EVs batteries must be at the intended state of charge at the departure time announced by the EV driver. Our goal is to exploit the potential of the EV batteries capacity as much as possible in order to permit a large area of solar panels, so that even on sunny days all PV power can be used to supply the building needs or the EV charging at the parking lot. A system architecture and collaboration protocols that account for uncertainties in EV behaviour are proposed. The proposed approach is proven in simulation covering one year period for three locations in different climatic regions of the US, resulting in the electricity bill reductions of 15.8%, 9.1% and 4.9% for California, New Jersey and Alaska, respectively. These results are compared to state-of-the-art research in combining V2B with PV or wind power generation. It is concluded that the achieved electricity bill reductions are superior to the state-of-the-art, because previous work is based on problem formulations that exploit only a part of the potential EV battery capacity.

Suggested Citation

  • Evgeny Nefedov & Seppo Sierla & Valeriy Vyatkin, 2018. "Internet of Energy Approach for Sustainable Use of Electric Vehicles as Energy Storage of Prosumer Buildings," Energies, MDPI, vol. 11(8), pages 1-18, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2165-:d:164516
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Xin Li & Xiaodi Zhang & Yuling Fan, 2019. "A Two-Step Framework for Energy Local Area Network Scheduling Problem with Electric Vehicles Based on Global–Local Optimization Method," Energies, MDPI, vol. 12(1), pages 1-17, January.
    2. Harri Aaltonen & Seppo Sierla & Rakshith Subramanya & Valeriy Vyatkin, 2021. "A Simulation Environment for Training a Reinforcement Learning Agent Trading a Battery Storage," Energies, MDPI, vol. 14(17), pages 1-20, September.
    3. Ghafoori, Mahdi & Abdallah, Moatassem & Kim, Serena, 2023. "Electricity peak shaving for commercial buildings using machine learning and vehicle to building (V2B) system," Applied Energy, Elsevier, vol. 340(C).
    4. Yingpei Liu & Yan Li & Haiping Liang & Jia He & Hanyang Cui, 2019. "Energy Routing Control Strategy for Integrated Microgrids Including Photovoltaic, Battery-Energy Storage and Electric Vehicles," Energies, MDPI, vol. 12(2), pages 1-16, January.
    5. Niko Karhula & Seppo Sierla & Valeriy Vyatkin, 2021. "Validating the Real-Time Performance of Distributed Energy Resources Participating on Primary Frequency Reserves," Energies, MDPI, vol. 14(21), pages 1-19, October.
    6. Kenji Araki & Yasuyuki Ota & Anju Maeda & Minoru Kumano & Kensuke Nishioka, 2023. "Solar Electric Vehicles as Energy Sources in Disaster Zones: Physical and Social Factors," Energies, MDPI, vol. 16(8), pages 1-25, April.
    7. Jordan P. Sausen & Alzenira R. Abaide & Juan C. Vasquez & Josep M. Guerrero, 2022. "Battery-Conscious, Economic, and Prioritization-Based Electric Vehicle Residential Scheduling," Energies, MDPI, vol. 15(10), pages 1-18, May.
    8. Harri Aaltonen & Seppo Sierla & Ville Kyrki & Mahdi Pourakbari-Kasmaei & Valeriy Vyatkin, 2022. "Bidding a Battery on Electricity Markets and Minimizing Battery Aging Costs: A Reinforcement Learning Approach," Energies, MDPI, vol. 15(14), pages 1-19, July.
    9. Muhammad Saad & Husan Ali & Huamei Liu & Shahbaz Khan & Haider Zaman & Bakht Muhammad Khan & Du Kai & Ju Yongfeng, 2018. "A dq -Domain Impedance Measurement Methodology for Three-Phase Converters in Distributed Energy Systems," Energies, MDPI, vol. 11(10), pages 1-15, October.
    10. Helindu Cumaratunga & Masaki Imanaka & Muneaki Kurimoto & Shigeyuki Sugimoto & Takeyoshi Kato, 2021. "Proposal of Priority Schemes for Controlling Electric Vehicle Charging and Discharging in a Workplace Power System with High Penetration of Photovoltaic Systems," Energies, MDPI, vol. 14(22), pages 1-23, November.
    11. Yuancheng Li & Pan Zhang & Yimeng Wang, 2018. "The Location Privacy Protection of Electric Vehicles with Differential Privacy in V2G Networks," Energies, MDPI, vol. 11(10), pages 1-17, October.

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