IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v153y2018icp278-286.html
   My bibliography  Save this article

The profitability of vehicle to grid for system participants - A case study from the Electricity Reliability Council of Texas

Author

Listed:
  • Bhandari, Vivek
  • Sun, Kaiyang
  • Homans, Frances

Abstract

Operating costs and market rules are likely to have an impact on the rewards of participating in a Vehicle to Grid system. This paper investigates these impacts by developing a model of a centralized Vehicle to Grid system and applying it to the 2015 wholesale electricity market in Texas (Houston Hub) for selling energy and capacity. Three scenarios are examined. In the first scenario, electric vehicles are paid based on a fixed retail market price; in the second, they are paid a time-varying retail market price; in the third, the virtual power plant shares 50% of its total reward with the participating vehicles. The results demonstrate that, while this system is always financially profitable to the virtual power plant and the system operator gets grid services, the electric vehicles could lose money. Further, results show that these vehicles with lower per unit output-battery cost could lose more money because of extensive battery over-use and insufficient reward at current market prices. Lower battery costs, subsidies for participation in this system, and more rewarding market products could all make their participation more economically viable.

Suggested Citation

  • Bhandari, Vivek & Sun, Kaiyang & Homans, Frances, 2018. "The profitability of vehicle to grid for system participants - A case study from the Electricity Reliability Council of Texas," Energy, Elsevier, vol. 153(C), pages 278-286.
  • Handle: RePEc:eee:energy:v:153:y:2018:i:c:p:278-286
    DOI: 10.1016/j.energy.2018.04.038
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421830642X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2018.04.038?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Paine, Nathan & Homans, Frances R. & Pollak, Melisa & Bielicki, Jeffrey M. & Wilson, Elizabeth J., 2014. "Why market rules matter: Optimizing pumped hydroelectric storage when compensation rules differ," Energy Economics, Elsevier, vol. 46(C), pages 10-19.
    2. 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.
    3. Noori, Mehdi & Zhao, Yang & Onat, Nuri C. & Gardner, Stephanie & Tatari, Omer, 2016. "Light-duty electric vehicles to improve the integrity of the electricity grid through Vehicle-to-Grid technology: Analysis of regional net revenue and emissions savings," Applied Energy, Elsevier, vol. 168(C), pages 146-158.
    4. Lund, Henrik & Kempton, Willett, 2008. "Integration of renewable energy into the transport and electricity sectors through V2G," Energy Policy, Elsevier, vol. 36(9), pages 3578-3587, September.
    5. Sekyung Han & Soohee Han, 2013. "Economic Feasibility of V2G Frequency Regulation in Consideration of Battery Wear," Energies, MDPI, vol. 6(2), pages 1-18, February.
    6. Weiller, C. & Neely, A., 2014. "Using electric vehicles for energy services: Industry perspectives," Energy, Elsevier, vol. 77(C), pages 194-200.
    7. Manbachi, M. & Sadu, A. & Farhangi, H. & Monti, A. & Palizban, A. & Ponci, F. & Arzanpour, S., 2016. "Impact of EV penetration on Volt–VAR Optimization of distribution networks using real-time co-simulation monitoring platform," Applied Energy, Elsevier, vol. 169(C), pages 28-39.
    8. Uddin, Kotub & Jackson, Tim & Widanage, Widanalage D. & Chouchelamane, Gael & Jennings, Paul A. & Marco, James, 2017. "On the possibility of extending the lifetime of lithium-ion batteries through optimal V2G facilitated by an integrated vehicle and smart-grid system," Energy, Elsevier, vol. 133(C), pages 710-722.
    9. Wang, Lu & Sharkh, Suleiman & Chipperfield, Andy, 2016. "Optimal coordination of vehicle-to-grid batteries and renewable generators in a distribution system," Energy, Elsevier, vol. 113(C), pages 1250-1264.
    10. Hardman, Scott & Chandan, Amrit & Tal, Gil & Turrentine, Tom, 2017. "The effectiveness of financial purchase incentives for battery electric vehicles – A review of the evidence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1100-1111.
    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. Shahbazitabar, Maryam & Abdi, Hamdi, 2018. "A novel priority-based stochastic unit commitment considering renewable energy sources and parking lot cooperation," Energy, Elsevier, vol. 161(C), pages 308-324.
    2. Loris Di Natale & Luca Funk & Martin Rüdisüli & Bratislav Svetozarevic & Giacomo Pareschi & Philipp Heer & Giovanni Sansavini, 2021. "The Potential of Vehicle-to-Grid to Support the Energy Transition: A Case Study on Switzerland," Energies, MDPI, vol. 14(16), pages 1-24, August.

    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. Zhao, Yang & Noori, Mehdi & Tatari, Omer, 2017. "Boosting the adoption and the reliability of renewable energy sources: Mitigating the large-scale wind power intermittency through vehicle to grid technology," Energy, Elsevier, vol. 120(C), pages 608-618.
    2. Shahbazitabar, Maryam & Abdi, Hamdi, 2018. "A novel priority-based stochastic unit commitment considering renewable energy sources and parking lot cooperation," Energy, Elsevier, vol. 161(C), pages 308-324.
    3. Sovacool, Benjamin K. & Kester, Johannes & Noel, Lance & Zarazua de Rubens, Gerardo, 2020. "Actors, business models, and innovation activity systems for vehicle-to-grid (V2G) technology: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    4. Bishop, Justin D.K. & Axon, Colin J. & Bonilla, David & Banister, David, 2016. "Estimating the grid payments necessary to compensate additional costs to prospective electric vehicle owners who provide vehicle-to-grid ancillary services," Energy, Elsevier, vol. 94(C), pages 715-727.
    5. Teixeira, Ana Carolina Rodrigues & Sodré, José Ricardo, 2016. "Simulation of the impacts on carbon dioxide emissions from replacement of a conventional Brazilian taxi fleet by electric vehicles," Energy, Elsevier, vol. 115(P3), pages 1617-1622.
    6. 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.
    7. Stef Proost & Mads Greaker & Cathrine Hagem, 2019. "Vehicle-to-Grid. Impacts on the electricity market and consumer cost of electric vehicles," Discussion Papers 903, Statistics Norway, Research Department.
    8. Godina, Radu & Rodrigues, Eduardo M.G. & Matias, João C.O. & Catalão, João P.S., 2016. "Smart electric vehicle charging scheduler for overloading prevention of an industry client power distribution transformer," Applied Energy, Elsevier, vol. 178(C), pages 29-42.
    9. Barone, G. & Buonomano, A. & Forzano, C. & Palombo, A. & Russo, G., 2023. "The role of energy communities in electricity grid balancing: A flexible tool for smart grid power distribution optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    10. Khemakhem, Siwar & Rekik, Mouna & Krichen, Lotfi, 2017. "A flexible control strategy of plug-in electric vehicles operating in seven modes for smoothing load power curves in smart grid," Energy, Elsevier, vol. 118(C), pages 197-208.
    11. Qiwei Xu & Jianshu Huang & Yue Han & Yun Yang & Lingyan Luo, 2020. "A Study on Electric Vehicles Participating in the Load Regulation of Urban Complexes," Energies, MDPI, vol. 13(11), pages 1-23, June.
    12. Liao, Zitong & Taiebat, Morteza & Xu, Ming, 2021. "Shared autonomous electric vehicle fleets with vehicle-to-grid capability: Economic viability and environmental co-benefits," Applied Energy, Elsevier, vol. 302(C).
    13. Luo, Yugong & Zhu, Tao & Wan, Shuang & Zhang, Shuwei & Li, Keqiang, 2016. "Optimal charging scheduling for large-scale EV (electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems," Energy, Elsevier, vol. 97(C), pages 359-368.
    14. Noel, Lance & Zarazua de Rubens, Gerardo & Kester, Johannes & Sovacool, Benjamin K., 2018. "Beyond emissions and economics: Rethinking the co-benefits of electric vehicles (EVs) and vehicle-to-grid (V2G)," Transport Policy, Elsevier, vol. 71(C), pages 130-137.
    15. Popović Vlado & Jereb Borut & Kilibarda Milorad & Andrejić Milan & Keshavarzsaleh Abolfazl & Dragan Dejan, 2018. "Electric Vehicles as Electricity Storages in Electric Power Systems," Logistics, Supply Chain, Sustainability and Global Challenges, Sciendo, vol. 9(2), pages 57-72, October.
    16. Rahman, Md Mustafizur & Gemechu, Eskinder & Oni, Abayomi Olufemi & Kumar, Amit, 2023. "The development of a techno-economic model for assessment of cost of energy storage for vehicle-to-grid applications in a cold climate," Energy, Elsevier, vol. 262(PA).
    17. 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.
    18. Khemakhem, Siwar & Rekik, Mouna & Krichen, Lotfi, 2019. "Double layer home energy supervision strategies based on demand response and plug-in electric vehicle control for flattening power load curves in a smart grid," Energy, Elsevier, vol. 167(C), pages 312-324.
    19. Ensslen, Axel & Ringler, Philipp & Dörr, Lasse & Jochem, Patrick & Zimmermann, Florian & Fichtner, Wolf, 2018. "Incentivizing smart charging: Modeling charging tariffs for electric vehicles in German and French electricity markets," MPRA Paper 91543, University Library of Munich, Germany, revised 17 Feb 2018.
    20. Huang, Shoujun & Yang, Jun & Li, Shanjun, 2017. "Black-Scholes option pricing strategy and risk-averse coordination for designing vehicle-to-grid reserve contracts," Energy, Elsevier, vol. 137(C), pages 325-335.

    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:eee:energy:v:153:y:2018:i:c:p:278-286. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.