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A systematic solution to quantify economic values of vehicle grid integration

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  • Zhang, Haifeng
  • Tian, Ming
  • Zhang, Cong
  • Wang, Bin
  • Wang, Dai

Abstract

Vehicle-Grid-Integration (VGI) supplies one of the potential benefit extensions for electric vehicles (EVs) to make use of their parking time, which enables the EVs to provide grid services while still meeting consumer driving needs. However, the costs, benefits and risks of VGI still remain unclear, which limits the development of the VGI to promote the interaction between the EV and grid. In this study, we propose an integrated framework to quantify and utilize the aggregate flexibility of the EVs to supply the grid services in electricity markets. The integrated solution includes five sub-modules that cover end-to-end functionalities from individual EV energy consumption estimation to final monetary values calculation of providing grid services. Both wholesale market and local level charging management are formulated in the optimization module. A predictive control algorithm is proposed to allocate power to individual vehicles in real time, considering uncertainties from dispatch signal and travel behavior. Simulation results from 10,000 EVs indicate that the proposed optimization methods can significantly reduce the system cost in both wholesale market and retail market. Local tariff optimization reduces the electricity cost by 24.4% compared to uncontrolled charging. Wholesale market optimization results show that $691 and $255 revenues can be captured by each EV in ERCOT and CAISO markets per year, although with a conservative assumption on battery throughput cost at 0.16$/kWh.

Suggested Citation

  • Zhang, Haifeng & Tian, Ming & Zhang, Cong & Wang, Bin & Wang, Dai, 2021. "A systematic solution to quantify economic values of vehicle grid integration," Energy, Elsevier, vol. 232(C).
    • Handle: RePEc:eee:energy:v:232:y:2021:i:c:s0360544221012548
    DOI: 10.1016/j.energy.2021.121006
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    References listed on IDEAS

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    1. 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).
    2. Schuller, Alexander & Flath, Christoph M. & Gottwalt, Sebastian, 2015. "Quantifying load flexibility of electric vehicles for renewable energy integration," Applied Energy, Elsevier, vol. 151(C), pages 335-344.
    3. Gomez-Gonzalez, M. & Hernandez, J.C. & Vera, D. & Jurado, F., 2020. "Optimal sizing and power schedule in PV household-prosumers for improving PV self-consumption and providing frequency containment reserve," Energy, Elsevier, vol. 191(C).
    4. Zachary A. Needell & James McNerney & Michael T. Chang & Jessika E. Trancik, 2016. "Potential for widespread electrification of personal vehicle travel in the United States," Nature Energy, Nature, vol. 1(9), pages 1-7, September.
    5. Saxena, Samveg & MacDonald, Jason & Moura, Scott, 2015. "Charging ahead on the transition to electric vehicles with standard 120V wall outlets," Applied Energy, Elsevier, vol. 157(C), pages 720-728.
    6. Matteo Muratori, 2018. "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," Nature Energy, Nature, vol. 3(3), pages 193-201, March.
    7. Hernández, J.C. & Sanchez-Sutil, F. & Muñoz-Rodríguez, F.J., 2019. "Design criteria for the optimal sizing of a hybrid energy storage system in PV household-prosumers to maximize self-consumption and self-sufficiency," Energy, Elsevier, vol. 186(C).
    8. Cong Zhang & Dai Wang & Bin Wang & Fan Tong, 2020. "Battery Degradation Minimization-Oriented Hybrid Energy Storage System for Electric Vehicles," Energies, MDPI, vol. 13(1), pages 1-21, January.
    9. Tarroja, Brian & Zhang, Li & Wifvat, Van & Shaffer, Brendan & Samuelsen, Scott, 2016. "Assessing the stationary energy storage equivalency of vehicle-to-grid charging battery electric vehicles," Energy, Elsevier, vol. 106(C), pages 673-690.
    10. Heuberger, Clara F. & Bains, Praveen K. & Mac Dowell, Niall, 2020. "The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment," Applied Energy, Elsevier, vol. 257(C).
    11. Nezamoddini, Nasim & Wang, Yong, 2016. "Risk management and participation planning of electric vehicles in smart grids for demand response," Energy, Elsevier, vol. 116(P1), pages 836-850.
    12. Rangaraju, Surendraprabu & De Vroey, Laurent & Messagie, Maarten & Mertens, Jan & Van Mierlo, Joeri, 2015. "Impacts of electricity mix, charging profile, and driving behavior on the emissions performance of battery electric vehicles: A Belgian case study," Applied Energy, Elsevier, vol. 148(C), pages 496-505.
    13. Zhang, Cong & Greenblatt, Jeffery B. & MacDougall, Pamela & Saxena, Samveg & Jayam Prabhakar, Aditya, 2020. "Quantifying the benefits of electric vehicles on the future electricity grid in the midwestern United States," Applied Energy, Elsevier, vol. 270(C).
    14. Fathabadi, Hassan, 2017. "Novel grid-connected solar/wind powered electric vehicle charging station with vehicle-to-grid technology," Energy, Elsevier, vol. 132(C), pages 1-11.
    15. Seddig, Katrin & Jochem, Patrick & Fichtner, Wolf, 2019. "Two-stage stochastic optimization for cost-minimal charging of electric vehicles at public charging stations with photovoltaics," Applied Energy, Elsevier, vol. 242(C), pages 769-781.
    16. Hernández, J.C. & Sanchez-Sutil, F. & Muñoz-Rodríguez, F.J. & Baier, C.R., 2020. "Optimal sizing and management strategy for PV household-prosumers with self-consumption/sufficiency enhancement and provision of frequency containment reserve," Applied Energy, Elsevier, vol. 277(C).
    17. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "Incorporating unit commitment aspects to the European electricity markets algorithm: An optimization model for the joint clearing of energy and reserve markets," Applied Energy, Elsevier, vol. 231(C), pages 235-258.
    18. Shi, Ruifeng & Li, Shaopeng & Zhang, Penghui & Lee, Kwang Y., 2020. "Integration of renewable energy sources and electric vehicles in V2G network with adjustable robust optimization," Renewable Energy, Elsevier, vol. 153(C), pages 1067-1080.
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    1. Yin, WanJun & Wen, Tao & Zhang, Chao, 2023. "Cooperative optimal scheduling strategy of electric vehicles based on dynamic electricity price mechanism," Energy, Elsevier, vol. 263(PA).

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