IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i24p9572-d1006027.html
   My bibliography  Save this article

Utilizing Rooftop Renewable Energy Potential for Electric Vehicle Charging Infrastructure Using Multi-Energy Hub Approach

Author

Listed:
  • Syed Taha Taqvi

    (Chemical Engineering Department, University of Waterloo, Waterloo, ON N2L 3G1, Canada
    ABen Hub Incorporated, Kitchener, ON N2E 0E1, Canada)

  • Ali Almansoori

    (Department of Chemical Engineering, Khalifa University of Science, Technology and Research (KUSTAR), Abu Dhabi P.O. Box 2533, United Arab Emirates)

  • Azadeh Maroufmashat

    (Chemical Engineering Department, University of Waterloo, Waterloo, ON N2L 3G1, Canada)

  • Ali Elkamel

    (Chemical Engineering Department, University of Waterloo, Waterloo, ON N2L 3G1, Canada
    Department of Chemical Engineering, Khalifa University of Science, Technology and Research (KUSTAR), Abu Dhabi P.O. Box 2533, United Arab Emirates)

Abstract

Electric vehicles (EV) have the potential to significantly reduce carbon emissions. Yet, the current electric vehicle charging infrastructure utilizes electricity generated from non-renewable sources. In this study, the rooftop area of structures is analyzed to assess electricity that can be generated through solar- and wind-based technologies. Consequently, planning an electric vehicle charging infrastructure that is powered through ‘clean’ energy sources is presented. We developed an optimal modeling framework for the consideration of Renewable Energy Technologies (RET) along with EV infrastructure. After examining the level of technology, a MATLAB image segmentation technique was used to assess the available rooftop area. In this study, two competitive objectives including the economic cost of the system and CO 2 emissions are considered. Three scenarios are examined to assess the potential of RET to meet the EV demand along with the Abu Dhabi city one while considering the life-cycle emission of RET and EV systems. When meeting only EV demand through Renewable Energy Technologies (RET), about 187 ktonnes CO 2 was reduced annually. On the other hand, the best economic option was still to utilize grid-connected electricity, yielding about 2.24 Mt CO 2 annually. In the scenario of meeting both 10% EV demand and all Abu Dhabi city electricity demand using RE, wind-based technology is only able to meet around 3%. Analysis carried out by studying EV penetration demonstrated the preference of using level 2 AC home chargers compared to other ones. When the EV penetration exceeds 25%, preference was observed for level 2 (AC public 3ϕ) chargers.

Suggested Citation

  • Syed Taha Taqvi & Ali Almansoori & Azadeh Maroufmashat & Ali Elkamel, 2022. "Utilizing Rooftop Renewable Energy Potential for Electric Vehicle Charging Infrastructure Using Multi-Energy Hub Approach," Energies, MDPI, vol. 15(24), pages 1-21, December.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9572-:d:1006027
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/24/9572/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/24/9572/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Egbue, Ona & Long, Suzanna, 2012. "Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions," Energy Policy, Elsevier, vol. 48(C), pages 717-729.
    2. Phap Vu Minh & Sang Le Quang & Manh-Hai Pham, 2021. "Technical Economic Analysis of Photovoltaic-Powered Electric Vehicle Charging Stations under Different Solar Irradiation Conditions in Vietnam," Sustainability, MDPI, vol. 13(6), pages 1-20, March.
    3. Shang, Yitong & Liu, Man & Shao, Ziyun & Jian, Linni, 2020. "Internet of smart charging points with photovoltaic Integration: A high-efficiency scheme enabling optimal dispatching between electric vehicles and power grids," Applied Energy, Elsevier, vol. 278(C).
    4. Huang, Pei & Ma, Zhenjun & Xiao, Longzhu & Sun, Yongjun, 2019. "Geographic Information System-assisted optimal design of renewable powered electric vehicle charging stations in high-density cities," Applied Energy, Elsevier, vol. 255(C).
    5. Liu, Jian, 2012. "Electric vehicle charging infrastructure assignment and power grid impacts assessment in Beijing," Energy Policy, Elsevier, vol. 51(C), pages 544-557.
    6. Mezher, Toufic & Dawelbait, Gihan & Abbas, Zeina, 2012. "Renewable energy policy options for Abu Dhabi: Drivers and barriers," Energy Policy, Elsevier, vol. 42(C), pages 315-328.
    7. Yu, Hang & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jia, Youwei & Jian, Linni, 2022. "Electric vehicles integration and vehicle-to-grid operation in active distribution grids: A comprehensive review on power architectures, grid connection standards and typical applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    8. Schroeder, Andreas & Traber, Thure, 2012. "The economics of fast charging infrastructure for electric vehicles," Energy Policy, Elsevier, vol. 43(C), pages 136-144.
    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. Fahad Saleh Al-Ismail & Md Shafiul Alam & Md Shafiullah & Md Ismail Hossain & Syed Masiur Rahman, 2023. "Impacts of Renewable Energy Generation on Greenhouse Gas Emissions in Saudi Arabia: A Comprehensive Review," Sustainability, MDPI, vol. 15(6), pages 1-19, March.

    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. Motoaki, Yutaka & Yi, Wenqi & Salisbury, Shawn, 2018. "Empirical analysis of electric vehicle fast charging under cold temperatures," Energy Policy, Elsevier, vol. 122(C), pages 162-168.
    2. Neaimeh, Myriam & Salisbury, Shawn D. & Hill, Graeme A. & Blythe, Philip T. & Scoffield, Don R. & Francfort, James E., 2017. "Analysing the usage and evidencing the importance of fast chargers for the adoption of battery electric vehicles," Energy Policy, Elsevier, vol. 108(C), pages 474-486.
    3. Makena Coffman & Paul Bernstein & Sherilyn Wee, 2017. "Electric vehicles revisited: a review of factors that affect adoption," Transport Reviews, Taylor & Francis Journals, vol. 37(1), pages 79-93, January.
    4. Wee, Sherilyn & Coffman, Makena & Allen, Scott, 2020. "EV driver characteristics: Evidence from Hawaii," Transport Policy, Elsevier, vol. 87(C), pages 33-40.
    5. Tan, Bing Qing & Kang, Kai & Zhong, Ray Y., 2023. "Electric vehicle charging infrastructure investment strategy analysis: State-owned versus private parking lots," Transport Policy, Elsevier, vol. 141(C), pages 54-71.
    6. Anders F. Jensen & Thomas K. Rasmussen & Carlo G. Prato, 2020. "A Route Choice Model for Capturing Driver Preferences When Driving Electric and Conventional Vehicles," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
    7. Nilsson, Måns & Nykvist, Björn, 2016. "Governing the electric vehicle transition – Near term interventions to support a green energy economy," Applied Energy, Elsevier, vol. 179(C), pages 1360-1371.
    8. Makena Coffman & Scott Allen & Sherilyn Wee, 2018. "Who are Driving Electric Vehicles? An analysis of factors that affect EV adoption in Hawaii," Working Papers 2018-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    9. Micari, Salvatore & Polimeni, Antonio & Napoli, Giuseppe & Andaloro, Laura & Antonucci, Vincenzo, 2017. "Electric vehicle charging infrastructure planning in a road network," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 98-108.
    10. Han, Liu & Wang, Shanyong & Zhao, Dingtao & Li, Jun, 2017. "The intention to adopt electric vehicles: Driven by functional and non-functional values," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 185-197.
    11. Akansha Jain & Masoud Karimi-Ghartemani, 2022. "Mitigating Adverse Impacts of Increased Electric Vehicle Charging on Distribution Transformers," Energies, MDPI, vol. 15(23), pages 1-26, November.
    12. Hsu, Chih-Wei & Fingerman, Kevin, 2021. "Public electric vehicle charger access disparities across race and income in California," Transport Policy, Elsevier, vol. 100(C), pages 59-67.
    13. Lin Ma & Yuefan Zhai & Tian Wu, 2019. "Operating Charging Infrastructure in China to Achieve Sustainable Transportation: The Choice between Company-Owned and Franchised Structures," Sustainability, MDPI, vol. 11(6), pages 1-22, March.
    14. Lei, Xiang & Yu, Hang & Shao, Ziyun & Jian, Linni, 2023. "Optimal bidding and coordinating strategy for maximal marginal revenue due to V2G operation: Distribution system operator as a key player in China's uncertain electricity markets," Energy, Elsevier, vol. 283(C).
    15. Xiaoli Sun & Zhengguo Li & Xiaolin Wang & Chengjiang Li, 2019. "Technology Development of Electric Vehicles: A Review," Energies, MDPI, vol. 13(1), pages 1-29, December.
    16. Li, Junqiang & Ren, Hao & Wang, Mingyue, 2021. "How to escape the dilemma of charging infrastructure construction? A multi-sectorial stochastic evolutionary game model," Energy, Elsevier, vol. 231(C).
    17. Tuballa, Maria Lorena & Abundo, Michael Lochinvar, 2016. "A review of the development of Smart Grid technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 710-725.
    18. Wu, Tian & Shang, Zhe & Tian, Xin & Wang, Shouyang, 2016. "How hyperbolic discounting preference affects Chinese consumers’ consumption choice between conventional and electric vehicles," Energy Policy, Elsevier, vol. 97(C), pages 400-413.
    19. Tian Wu & Bohan Zeng & Yali He & Xin Tian & Xunmin Ou, 2017. "Sustainable Governance for the Opened Electric Vehicle Charging and Upgraded Facilities Market," Sustainability, MDPI, vol. 9(11), pages 1-22, November.
    20. Lingling Shi & Suresh P. Sethi & Metin Çakanyıldırım, 2022. "Promoting electric vehicles: Reducing charging inconvenience and price via station and consumer subsidies," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4333-4350, 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:15:y:2022:i:24:p:9572-:d:1006027. 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.