IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i8p2165-d164516.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/8/2165/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/8/2165/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alipour, Manijeh & Mohammadi-Ivatloo, Behnam & Moradi-Dalvand, Mohammad & Zare, Kazem, 2017. "Stochastic scheduling of aggregators of plug-in electric vehicles for participation in energy and ancillary service markets," Energy, Elsevier, vol. 118(C), pages 1168-1179.
    2. Rezkalla, Michel & Zecchino, Antonio & Martinenas, Sergejus & Prostejovsky, Alexander M. & Marinelli, Mattia, 2018. "Comparison between synthetic inertia and fast frequency containment control based on single phase EVs in a microgrid," Applied Energy, Elsevier, vol. 210(C), pages 764-775.
    3. Leehter Yao & Zolboo Damiran & Wei Hong Lim, 2017. "Optimal Charging and Discharging Scheduling for Electric Vehicles in a Parking Station with Photovoltaic System and Energy Storage System," Energies, MDPI, vol. 10(4), pages 1-20, April.
    4. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2018. "Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule," Applied Energy, Elsevier, vol. 210(C), pages 1188-1206.
    5. Han, Sekyung & Han, Soohee & Aki, Hirohisa, 2014. "A practical battery wear model for electric vehicle charging applications," Applied Energy, Elsevier, vol. 113(C), pages 1100-1108.
    6. Shang, Duo (Rick) & Sun, Guodong, 2016. "Electricity-price arbitrage with plug-in hybrid electric vehicle: Gain or loss?," Energy Policy, Elsevier, vol. 95(C), pages 402-410.
    7. Gough, Rebecca & Dickerson, Charles & Rowley, Paul & Walsh, Chris, 2017. "Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage," Applied Energy, Elsevier, vol. 192(C), pages 12-23.
    8. Honarmand, Masoud & Zakariazadeh, Alireza & Jadid, Shahram, 2014. "Optimal scheduling of electric vehicles in an intelligent parking lot considering vehicle-to-grid concept and battery condition," Energy, Elsevier, vol. 65(C), pages 572-579.
    9. Aneke, Mathew & Wang, Meihong, 2016. "Energy storage technologies and real life applications – A state of the art review," Applied Energy, Elsevier, vol. 179(C), pages 350-377.
    10. Mwasilu, Francis & Justo, Jackson John & Kim, Eun-Kyung & Do, Ton Duc & Jung, Jin-Woo, 2014. "Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 501-516.
    11. Chaouachi, Aymen & Bompard, Ettore & Fulli, Gianluca & Masera, Marcelo & De Gennaro, Michele & Paffumi, Elena, 2016. "Assessment framework for EV and PV synergies in emerging distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 719-728.
    12. Luo, Xing & Wang, Jihong & Dooner, Mark & Clarke, Jonathan, 2015. "Overview of current development in electrical energy storage technologies and the application potential in power system operation," Applied Energy, Elsevier, vol. 137(C), pages 511-536.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    2. Shepero, Mahmoud & Munkhammar, Joakim & Widén, Joakim & Bishop, Justin D.K. & Boström, Tobias, 2018. "Modeling of photovoltaic power generation and electric vehicles charging on city-scale: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 61-71.
    3. Heilmann, C. & Friedl, G., 2021. "Factors influencing the economic success of grid-to-vehicle and vehicle-to-grid applications—A review and meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    4. Nunes, Pedro & Figueiredo, Raquel & Brito, Miguel C., 2016. "The use of parking lots to solar-charge electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 679-693.
    5. Barone, Giovanni & Buonomano, Annamaria & Forzano, Cesare & Giuzio, Giovanni Francesco & Palombo, Adolfo & Russo, Giuseppe, 2022. "Energy virtual networks based on electric vehicles for sustainable buildings: System modelling for comparative energy and economic analyses," Energy, Elsevier, vol. 242(C).
    6. Miguel J. Prieto & Juan Á. Martínez & Rogelio Peón & Lourdes Á. Barcia & Fernando Nuño, 2017. "On the Convenience of Using Simulation Models to Optimize the Control Strategy of Molten-Salt Heat Storage Systems in Solar Thermal Power Plants," Energies, MDPI, vol. 10(7), pages 1-17, July.
    7. Nagel, Niels Oliver & Jåstad, Eirik Ogner & Martinsen, Thomas, 2024. "The grid benefits of vehicle-to-grid in Norway and Denmark: An analysis of home- and public parking potentials," Energy, Elsevier, vol. 293(C).
    8. Meng, Hui & Wang, Meihong & Olumayegun, Olumide & Luo, Xiaobo & Liu, Xiaoyan, 2019. "Process design, operation and economic evaluation of compressed air energy storage (CAES) for wind power through modelling and simulation," Renewable Energy, Elsevier, vol. 136(C), pages 923-936.
    9. Pearre, Nathaniel S. & Ribberink, Hajo, 2019. "Review of research on V2X technologies, strategies, and operations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 61-70.
    10. Madani, Seyyedreza & Pineau, Pierre-Olivier, 2024. "Investment in vehicle-to-grid and distributed energy resources: Distributor versus prosumer perspectives and the impact of rate structures," Utilities Policy, Elsevier, vol. 88(C).
    11. Ruben Garruto & Michela Longo & Wahiba Yaïci & Federica Foiadelli, 2020. "Connecting Parking Facilities to the Electric Grid: A Vehicle-to-Grid Feasibility Study in a Railway Station’s Car Park," Energies, MDPI, vol. 13(12), pages 1-23, June.
    12. Wang, Liang & Lin, Xipeng & Chai, Lei & Peng, Long & Yu, Dong & Chen, Haisheng, 2019. "Cyclic transient behavior of the Joule–Brayton based pumped heat electricity storage: Modeling and analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 523-534.
    13. Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2019. "A unified model to optimize configuration of battery energy storage systems with multiple types of batteries," Energy, Elsevier, vol. 176(C), pages 552-560.
    14. Su, Chengguo & Cheng, Chuntian & Wang, Peilin & Shen, Jianjian & Wu, Xinyu, 2019. "Optimization model for long-distance integrated transmission of wind farms and pumped-storage hydropower plants," Applied Energy, Elsevier, vol. 242(C), pages 285-293.
    15. Das, H.S. & Rahman, M.M. & Li, S. & Tan, C.W., 2020. "Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    16. Yong, Jia Ying & Ramachandaramurthy, Vigna K. & Tan, Kang Miao & Mithulananthan, N., 2015. "A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 365-385.
    17. Liu, Shuai & Wei, Li & Wang, Huai, 2020. "Review on reliability of supercapacitors in energy storage applications," Applied Energy, Elsevier, vol. 278(C).
    18. Hunt, Julian David & Zakeri, Behnam & Falchetta, Giacomo & Nascimento, Andreas & Wada, Yoshihide & Riahi, Keywan, 2020. "Mountain Gravity Energy Storage: A new solution for closing the gap between existing short- and long-term storage technologies," Energy, Elsevier, vol. 190(C).
    19. Gimelli, A. & Mottola, F. & Muccillo, M. & Proto, D. & Amoresano, A. & Andreotti, A. & Langella, G., 2019. "Optimal configuration of modular cogeneration plants integrated by a battery energy storage system providing peak shaving service," Applied Energy, Elsevier, vol. 242(C), pages 974-993.
    20. Jaržemskis Andrius & Jaržemskienė Ilona, 2022. "European Green Deal Implications on Country Level Energy Consumption," Folia Oeconomica Stetinensia, Sciendo, vol. 22(2), pages 97-122, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2165-:d:164516. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.