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Evaluation of smart charging for electric vehicle-to-building integration: A case study

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  • Heredia, Willy Bernal
  • Chaudhari, Kalpesh
  • Meintz, Andrew
  • Jun, Myungsoo
  • Pless, Shanti

Abstract

Higher electric vehicle (EV) adoption will stress the importance of demand flexibility to achieve more economic, efficient, and reliable grid operation. Charging technologies will be paramount in shifting temporally to better fit the variable generation of wind and solar. Therefore, analysis is warranted on the benefits of EV charge scheduling with respect to installation cost, operation cost, difficulty of implementation, and grid flexibility. We tackle this by analyzing the cost savings of implementing an EV charge scheduling infrastructure to reduce demand charges and installation costs. In this paper, we analyze a case study for operation of 16 level 2 chargers and 1 fast charger for two different building types. We then evaluate various test phases for controlling building and charging loads using an adaptive charging network (ACN) algorithm to characterize the ACN’s potential to reduce overall project cost.

Suggested Citation

  • Heredia, Willy Bernal & Chaudhari, Kalpesh & Meintz, Andrew & Jun, Myungsoo & Pless, Shanti, 2020. "Evaluation of smart charging for electric vehicle-to-building integration: A case study," Applied Energy, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:appene:v:266:y:2020:i:c:s0306261920303159
    DOI: 10.1016/j.apenergy.2020.114803
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    References listed on IDEAS

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    1. Xydas, Erotokritos & Marmaras, Charalampos & Cipcigan, Liana M. & Jenkins, Nick & Carroll, Steve & Barker, Myles, 2016. "A data-driven approach for characterising the charging demand of electric vehicles: A UK case study," Applied Energy, Elsevier, vol. 162(C), pages 763-771.
    2. van der Kam, Mart & van Sark, Wilfried, 2015. "Smart charging of electric vehicles with photovoltaic power and vehicle-to-grid technology in a microgrid; a case study," Applied Energy, Elsevier, vol. 152(C), pages 20-30.
    3. Ioakimidis, Christos S. & Thomas, Dimitrios & Rycerski, Pawel & Genikomsakis, Konstantinos N., 2018. "Peak shaving and valley filling of power consumption profile in non-residential buildings using an electric vehicle parking lot," Energy, Elsevier, vol. 148(C), pages 148-158.
    4. Zhao, Xiaoli & Cai, Qiong & Li, Shujie & Ma, Chunbo, 2018. "Public preferences for biomass electricity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 242-253.
    5. Iuliana SIMONCA (BOTHA) & Simona Vasilica OPREA & Adina UTA & Ion LUNGU & Osman Bulent TOR, 2018. "Data Model for Electricity Consumption Management," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 9(1), pages 48-57.
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    Cited by:

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    2. Zhou, Yuekuan, 2024. "AI-driven battery ageing prediction with distributed renewable community and E-mobility energy sharing," Renewable Energy, Elsevier, vol. 225(C).
    3. Liu, Xiaochen & Fu, Zhi & Qiu, Siyuan & Li, Shaojie & Zhang, Tao & Liu, Xiaohua & Jiang, Yi, 2023. "Building-centric investigation into electric vehicle behavior: A survey-based simulation method for charging system design," Energy, Elsevier, vol. 271(C).
    4. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M., 2021. "An energy paradigm transition framework from negative towards positive district energy sharing networks—Battery cycling aging, advanced battery management strategies, flexible vehicles-to-buildings in," Applied Energy, Elsevier, vol. 288(C).
    5. Lo Piano, S. & Smith, S.T., 2022. "Energy demand and its temporal flexibility: Approaches, criticalities and ways forward," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    6. Zhou, Yuekuan & Liu, Xiaohua & Zhao, Qianchuan, 2024. "A stochastic vehicle schedule model for demand response and grid flexibility in a renewable-building-e-transportation-microgrid," Renewable Energy, Elsevier, vol. 221(C).
    7. Nandan Gopinathan & Prabhakar Karthikeyan Shanmugam, 2022. "Energy Anxiety in Decentralized Electricity Markets: A Critical Review on EV Models," Energies, MDPI, vol. 15(14), pages 1-40, July.

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