IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i19p5095-d421845.html
   My bibliography  Save this article

A Case Study in Qatar for Optimal Energy Management of an Autonomous Electric Vehicle Fast Charging Station with Multiple Renewable Energy and Storage Systems

Author

Listed:
  • Abdulla Al Wahedi

    (Division of Sustainable Development (DSD), College of Science and Engineering (CSE), Hamad Bin Khalifa University (HBKU), Education City 5825, Doha, Qatar)

  • Yusuf Bicer

    (Division of Sustainable Development (DSD), College of Science and Engineering (CSE), Hamad Bin Khalifa University (HBKU), Education City 5825, Doha, Qatar)

Abstract

E-Mobility deployment has attained increased interest during recent years in various countries all over the world. This interest has focused mainly on reducing the reliance on fossil fuel-based means of transportation and decreasing the harmful emissions produced from this sector. To secure the electricity required to satisfy Electric Vehicles’ (EVs’) charging needs without expanding or overloading the existing electricity infrastructure, stand-alone charging stations powered by renewable sources are considered as a reasonable solution. This paper investigates the simulation of the optimal energy management of a proposed grid-independent, multi-generation, fast-charging station in the State of Qatar, which comprises hybrid wind, solar and biofuel systems along with ammonia, hydrogen and battery storage units. The study aims to assess the optimal sizing of the solar, wind and biofuel units to be incorporated in the design along with the optimal ammonia, hydrogen and battery storage capacities to fulfill the daily EV demand in an uninterruptable manner. The main objective is to fast-charge a minimum of 50 EVs daily, while the constraints are the intermittent and volatile nature of renewable energy sources, the stochastic nature of EV demand, local meteorological conditions and land space limitations. The results show that the selection of a 468 kWp concentrated photovoltaic thermal plant, 250 kW-rated wind turbine, 10 kW biodiesel power generator unit and 595 kWh battery storage system, along with the on-site production of hydrogen and ammonia, to generate 200 kW power via fuel cells can achieve the desired target, with a total halt of on-site hydrogen and ammonia production during October and November and 50% reduction during December.

Suggested Citation

  • Abdulla Al Wahedi & Yusuf Bicer, 2020. "A Case Study in Qatar for Optimal Energy Management of an Autonomous Electric Vehicle Fast Charging Station with Multiple Renewable Energy and Storage Systems," Energies, MDPI, vol. 13(19), pages 1-26, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5095-:d:421845
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/19/5095/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/19/5095/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sadeghi-Barzani, Payam & Rajabi-Ghahnavieh, Abbas & Kazemi-Karegar, Hosein, 2014. "Optimal fast charging station placing and sizing," Applied Energy, Elsevier, vol. 125(C), pages 289-299.
    2. Wu, Di & Radhakrishnan, Nikitha & Huang, Sen, 2019. "A hierarchical charging control of plug-in electric vehicles with simple flexibility model," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Gong, Lili & Cao, Wu & Liu, Kangli & Yu, Yue & Zhao, Jianfeng, 2020. "Demand responsive charging strategy of electric vehicles to mitigate the volatility of renewable energy sources," Renewable Energy, Elsevier, vol. 156(C), pages 665-676.
    4. Gouveia, João Pedro & Dias, Luís & Martins, Inês & Seixas, Júlia, 2014. "Effects of renewables penetration on the security of Portuguese electricity supply," Applied Energy, Elsevier, vol. 123(C), pages 438-447.
    5. Carlos Méndez & Yusuf Bicer, 2019. "Qatar’s Wind Energy Potential with Associated Financial and Environmental Benefits for the Natural Gas Industry," Energies, MDPI, vol. 12(17), pages 1-19, August.
    6. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "An optimal investment planning framework for multiple distributed generation units in industrial distribution systems," Applied Energy, Elsevier, vol. 124(C), pages 62-72.
    7. Goli, P. & Shireen, W., 2014. "PV powered smart charging station for PHEVs," Renewable Energy, Elsevier, vol. 66(C), pages 280-287.
    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. Hidab Hamwi & Rajeev Alasseri & Sara Aldei & Mariam Al-Kandari, 2022. "A Pilot Study of Electrical Vehicle Performance, Efficiency, and Limitation in Kuwait’s Harsh Weather and Environment," Energies, MDPI, vol. 15(20), pages 1-14, October.
    2. Evgeny Solomin & Shanmuga Priya Selvanathan & Sudhakar Kumarasamy & Anton Kovalyov & Ramyashree Maddappa Srinivasa, 2021. "The Comparison of Solar-Powered Hydrogen Closed-Cycle System Capacities for Selected Locations," Energies, MDPI, vol. 14(9), pages 1-18, May.
    3. Al Wahedi, Abdulla & Bicer, Yusuf, 2022. "Techno-economic optimization of novel stand-alone renewables-based electric vehicle charging stations in Qatar," Energy, Elsevier, vol. 243(C).
    4. Roberto Ruggieri & Marco Ruggeri & Giuliana Vinci & Stefano Poponi, 2021. "Electric Mobility in a Smart City: European Overview," Energies, MDPI, vol. 14(2), pages 1-29, January.

    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. Muratori, Matteo & Elgqvist, Emma & Cutler, Dylan & Eichman, Joshua & Salisbury, Shawn & Fuller, Zachary & Smart, John, 2019. "Technology solutions to mitigate electricity cost for electric vehicle DC fast charging," Applied Energy, Elsevier, vol. 242(C), pages 415-423.
    2. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    3. Natascia Andrenacci & Roberto Ragona & Antonino Genovese, 2020. "Evaluation of the Instantaneous Power Demand of an Electric Charging Station in an Urban Scenario," Energies, MDPI, vol. 13(11), pages 1-19, May.
    4. Luiz Almeida & Ana Soares & Pedro Moura, 2023. "A Systematic Review of Optimization Approaches for the Integration of Electric Vehicles in Public Buildings," Energies, MDPI, vol. 16(13), pages 1-26, June.
    5. Sun, Siyang & Yang, Qiang & Ma, Jin & Ferré, Adrià Junyent & Yan, Wenjun, 2020. "Hierarchical planning of PEV charging facilities and DGs under transportation-power network couplings," Renewable Energy, Elsevier, vol. 150(C), pages 356-369.
    6. Morro-Mello, Igoor & Padilha-Feltrin, Antonio & Melo, Joel D. & Heymann, Fabian, 2021. "Spatial connection cost minimization of EV fast charging stations in electric distribution networks using local search and graph theory," Energy, Elsevier, vol. 235(C).
    7. Fachrizal, Reza & Shepero, Mahmoud & Åberg, Magnus & Munkhammar, Joakim, 2022. "Optimal PV-EV sizing at solar powered workplace charging stations with smart charging schemes considering self-consumption and self-sufficiency balance," Applied Energy, Elsevier, vol. 307(C).
    8. 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.
    9. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    10. 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).
    11. Davidov, Sreten & Pantoš, Miloš, 2017. "Planning of electric vehicle infrastructure based on charging reliability and quality of service," Energy, Elsevier, vol. 118(C), pages 1156-1167.
    12. Se Hoon Baik & Young Gyu Jin & Yong Tae Yoon, 2018. "Determining Equipment Capacity of Electric Vehicle Charging Station Operator for Profit Maximization," Energies, MDPI, vol. 11(9), pages 1-15, September.
    13. Arlt, Marie-Louise & Astier, Nicolas, 2023. "Do retail businesses have efficient incentives to invest in public charging stations for electric vehicles?," Energy Economics, Elsevier, vol. 124(C).
    14. García-Triviño, Pablo & Torreglosa, Juan P. & Fernández-Ramírez, Luis M. & Jurado, Francisco, 2016. "Control and operation of power sources in a medium-voltage direct-current microgrid for an electric vehicle fast charging station with a photovoltaic and a battery energy storage system," Energy, Elsevier, vol. 115(P1), pages 38-48.
    15. Kim, Hyunjung & Kim, Dae-Wook & Kim, Man-Keun, 2022. "Economics of charging infrastructure for electric vehicles in Korea," Energy Policy, Elsevier, vol. 164(C).
    16. Sultana, U. & Khairuddin, Azhar B. & Sultana, Beenish & Rasheed, Nadia & Qazi, Sajid Hussain & Malik, Nimra Riaz, 2018. "Placement and sizing of multiple distributed generation and battery swapping stations using grasshopper optimizer algorithm," Energy, Elsevier, vol. 165(PA), pages 408-421.
    17. Globisch, Joachim & Plötz, Patrick & Dütschke, Elisabeth & Wietschel, Martin, 2018. "Consumer evaluation of public charging infrastructure for electric vehicles," Working Papers "Sustainability and Innovation" S13/2018, Fraunhofer Institute for Systems and Innovation Research (ISI).
    18. Zhou, Guangyou & Zhu, Zhiwei & Luo, Sumei, 2022. "Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm," Energy, Elsevier, vol. 247(C).
    19. Alya AlHammadi & Nasser Al-Saif & Ameena Saad Al-Sumaiti & Mousa Marzband & Tareefa Alsumaiti & Ehsan Heydarian-Forushani, 2022. "Techno-Economic Analysis of Hybrid Renewable Energy Systems Designed for Electric Vehicle Charging: A Case Study from the United Arab Emirates," Energies, MDPI, vol. 15(18), pages 1-20, September.
    20. Milan Straka & Pasquale De Falco & Gabriella Ferruzzi & Daniela Proto & Gijs van der Poel & Shahab Khormali & v{L}ubov{s} Buzna, 2019. "Predicting popularity of EV charging infrastructure from GIS data," Papers 1910.02498, arXiv.org.

    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:13:y:2020:i:19:p:5095-:d:421845. 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.