IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v162y2022ics1364032122002969.html
   My bibliography  Save this article

A probabilistic framework for the techno-economic assessment of smart energy hubs for electric vehicle charging

Author

Listed:
  • George-Williams, H.
  • Wade, N.
  • Carpenter, R.N.

Abstract

Smart energy hubs (Smart Hubs) equipped with Vehicle-to-Grid (V2G) charging, photovoltaic (PV) energy generation, and hydrogen storage capabilities, are an emerging technology with potential to alleviate the impact of electric vehicles (EV) on the electricity grid. Their operation, however, is characterised by intermittent PV energy generation, as well as uncertainties in EV traffic and driver preference. These uncertainties, when combined with the need to maximise their financial return while guaranteeing driver satisfaction, yields a challenging decision-making problem. This paper presents a novel Monte-Carlo-based modelling and computational framework for simulating the operation of Smart Hubs — providing a means for a holistic assessment of their technical and financial viability. The framework utilises a compact and representative mathematical model, accounting for power losses, PV module degradation, variability in EV uptake, price inflation, driver preference, and diversity in charge points and EVs. It provides a comprehensive approach for dealing with uncertainties and dependencies in EV data while being built on an energy management algorithm that maximises revenue generation, ensures driver satisfaction, and preserves battery life. The energy management problem is formulated as a mixed-integer linear programming problem constituting a business case that includes an adequate V2G reward model for drivers. To demonstrate its applicability, the framework was used to assess the financial viability of a fleet management site, for various caps on vehicle stay at the site. From the assessment, controlled charging was found to be more financially rewarding in all cases, yielding between 1.7% and 3.1% more revenue than uncontrolled charging. The self-consumption of the site was found to be nearly 100%, due mainly to local load shifting and dispatchable hydrogen generation. V2G injection was, however, negligible — suggesting its unattractiveness for sites that do not participate in the demand side response market. Overall, the numerical results obtained validate the applicability of the proposed framework as a decision-support tool in the sustainable design and operation of Smart Hubs for EV charging.

Suggested Citation

  • George-Williams, H. & Wade, N. & Carpenter, R.N., 2022. "A probabilistic framework for the techno-economic assessment of smart energy hubs for electric vehicle charging," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    • Handle: RePEc:eee:rensus:v:162:y:2022:i:c:s1364032122002969
    DOI: 10.1016/j.rser.2022.112386
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032122002969
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2022.112386?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. Shams, Mohammad H. & Shahabi, Majid & Khodayar, Mohammad E., 2018. "Stochastic day-ahead scheduling of multiple energy Carrier microgrids with demand response," Energy, Elsevier, vol. 155(C), pages 326-338.
    2. George-Williams, Hindolo & Patelli, Edoardo, 2016. "A hybrid load flow and event driven simulation approach to multi-state system reliability evaluation," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 351-367.
    3. van Noortwijk, J.M. & van der Weide, J.A.M. & Kallen, M.J. & Pandey, M.D., 2007. "Gamma processes and peaks-over-threshold distributions for time-dependent reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1651-1658.
    4. 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.
    5. 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.
    6. Chandra Mouli, G.R. & Bauer, P. & Zeman, M., 2016. "System design for a solar powered electric vehicle charging station for workplaces," Applied Energy, Elsevier, vol. 168(C), pages 434-443.
    7. Figueiredo, Raquel & Nunes, Pedro & Brito, Miguel C., 2017. "The feasibility of solar parking lots for electric vehicles," Energy, Elsevier, vol. 140(P1), pages 1182-1197.
    8. Narayan, Nishant & Papakosta, Thekla & Vega-Garita, Victor & Qin, Zian & Popovic-Gerber, Jelena & Bauer, Pavol & Zeman, Miroslav, 2018. "Estimating battery lifetimes in Solar Home System design using a practical modelling methodology," Applied Energy, Elsevier, vol. 228(C), pages 1629-1639.
    9. Ommen, Torben & Markussen, Wiebke Brix & Elmegaard, Brian, 2014. "Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling," Energy, Elsevier, vol. 74(C), pages 109-118.
    10. Mohammadi Landi, Meysam & Mohammadi, Mohammad & Rastegar, Mohammad, 2018. "Simultaneous determination of optimal capacity and charging profile of plug-in electric vehicle parking lots in distribution systems," Energy, Elsevier, vol. 158(C), pages 504-511.
    11. Hafez, Omar & Bhattacharya, Kankar, 2017. "Optimal design of electric vehicle charging stations considering various energy resources," Renewable Energy, Elsevier, vol. 107(C), pages 576-589.
    12. Koehler, K. J. & Symanowski, J. T., 1995. "Constructing Multivariate Distributions with Specific Marginal Distributions," Journal of Multivariate Analysis, Elsevier, vol. 55(2), pages 261-282, November.
    13. Lee, Sangyoon & Choi, Dae-Hyun, 2021. "Dynamic pricing and energy management for profit maximization in multiple smart electric vehicle charging stations: A privacy-preserving deep reinforcement learning approach," Applied Energy, Elsevier, vol. 304(C).
    14. Mehrjerdi, Hasan & Hemmati, Reza, 2020. "Coordination of vehicle-to-home and renewable capacity resources for energy management in resilience and self-healing building," Renewable Energy, Elsevier, vol. 146(C), pages 568-579.
    15. Daryabari, Mohamad K. & Keypour, Reza & Golmohamadi, Hessam, 2021. "Robust self-scheduling of parking lot microgrids leveraging responsive electric vehicles," Applied Energy, Elsevier, vol. 290(C).
    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. Sagar Hossain & Md. Rokonuzzaman & Kazi Sajedur Rahman & A. K. M. Ahasan Habib & Wen-Shan Tan & Md Mahmud & Shahariar Chowdhury & Sittiporn Channumsin, 2023. "Grid-Vehicle-Grid (G2V2G) Efficient Power Transmission: An Overview of Concept, Operations, Benefits, Concerns, and Future Challenges," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
    2. Anna Auza & Ehsan Asadi & Behrang Chenari & Manuel Gameiro da Silva, 2023. "A Systematic Review of Uncertainty Handling Approaches for Electric Grids Considering Electrical Vehicles," Energies, MDPI, vol. 16(13), pages 1-25, June.

    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. Seddig, Katrin & Jochem, Patrick & Fichtner, Wolf, 2017. "Integrating renewable energy sources by electric vehicle fleets under uncertainty," Energy, Elsevier, vol. 141(C), pages 2145-2153.
    2. Eltoumi, Fouad M. & Becherif, Mohamed & Djerdir, Abdesslem & Ramadan, Haitham.S., 2021. "The key issues of electric vehicle charging via hybrid power sources: Techno-economic viability, analysis, and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    3. Hoarau, Quentin & Perez, Yannick, 2018. "Interactions between electric mobility and photovoltaic generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 510-522.
    4. Schröder, M. & Abdin, Z. & Mérida, W., 2020. "Optimization of distributed energy resources for electric vehicle charging and fuel cell vehicle refueling," Applied Energy, Elsevier, vol. 277(C).
    5. Viviani Caroline Onishi & Carlos Henggeler Antunes & João Pedro Fernandes Trovão, 2020. "Optimal Energy and Reserve Market Management in Renewable Microgrid-PEVs Parking Lot Systems: V2G, Demand Response and Sustainability Costs," Energies, MDPI, vol. 13(8), pages 1-24, April.
    6. Ghotge, Rishabh & van Wijk, Ad & Lukszo, Zofia, 2021. "Off-grid solar charging of electric vehicles at long-term parking locations," Energy, Elsevier, vol. 227(C).
    7. Raja S, Charles & Kumar N M, Vijaya & J, Senthil kumar & Nesamalar J, Jeslin Drusila, 2021. "Enhancing system reliability by optimally integrating PHEV charging station and renewable distributed generators: A Bi-Level programming approach," Energy, Elsevier, vol. 229(C).
    8. Aminu Bugaje & Mathias Ehrenwirth & Christoph Trinkl & Wilfried Zörner, 2021. "Electric Two-Wheeler Vehicle Integration into Rural Off-Grid Photovoltaic System in Kenya," Energies, MDPI, vol. 14(23), pages 1-27, November.
    9. Mohd Bilal & Ibrahim Alsaidan & Muhannad Alaraj & Fahad M. Almasoudi & Mohammad Rizwan, 2022. "Techno-Economic and Environmental Analysis of Grid-Connected Electric Vehicle Charging Station Using AI-Based Algorithm," Mathematics, MDPI, vol. 10(6), pages 1-40, March.
    10. Mittelviefhaus, Moritz & Pareschi, Giacomo & Allan, James & Georges, Gil & Boulouchos, Konstantinos, 2021. "Optimal investment and scheduling of residential multi-energy systems including electric mobility: A cost-effective approach to climate change mitigation," Applied Energy, Elsevier, vol. 301(C).
    11. Aqib Shafiq & Sheeraz Iqbal & Salman Habib & Atiq ur Rehman & Anis ur Rehman & Ali Selim & Emad M. Ahmed & Salah Kamel, 2022. "Solar PV-Based Electric Vehicle Charging Station for Security Bikes: A Techno-Economic and Environmental Analysis," Sustainability, MDPI, vol. 14(21), pages 1-18, October.
    12. Shepero, Mahmoud & Munkhammar, Joakim & Widén, Joakim & Bishop, Justin D.K. & Boström, Tobias, 2018. "Modeling of photovoltaic power generation and electric vehicles charging on city-scale: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 61-71.
    13. Dileep, G., 2020. "A survey on smart grid technologies and applications," Renewable Energy, Elsevier, vol. 146(C), pages 2589-2625.
    14. Sebastian Szymon Grzesiak & Adam Sulich, 2023. "Electromobility: Logistics and Business Ecosystem Perspectives Review," Energies, MDPI, vol. 16(21), pages 1-27, October.
    15. Bhatti, Abdul Rauf & Salam, Zainal, 2018. "A rule-based energy management scheme for uninterrupted electric vehicles charging at constant price using photovoltaic-grid system," Renewable Energy, Elsevier, vol. 125(C), pages 384-400.
    16. Kyuho Maeng & Sungmin Ko & Jungwoo Shin & Youngsang Cho, 2020. "How Much Electricity Sharing Will Electric Vehicle Owners Allow from Their Battery? Incorporating Vehicle-to-Grid Technology and Electricity Generation Mix," Energies, MDPI, vol. 13(16), pages 1-25, August.
    17. Qiongjie Dai & Jicheng Liu & Qiushuang Wei, 2019. "Optimal Photovoltaic/Battery Energy Storage/Electric Vehicle Charging Station Design Based on Multi-Agent Particle Swarm Optimization Algorithm," Sustainability, MDPI, vol. 11(7), pages 1-21, April.
    18. Gheorghe Badea & Raluca-Andreea Felseghi & Mihai Varlam & Constantin Filote & Mihai Culcer & Mariana Iliescu & Maria Simona Răboacă, 2018. "Design and Simulation of Romanian Solar Energy Charging Station for Electric Vehicles," Energies, MDPI, vol. 12(1), pages 1-16, December.
    19. Paterakis, Nikolaos G. & Gibescu, Madeleine, 2016. "A methodology to generate power profiles of electric vehicle parking lots under different operational strategies," Applied Energy, Elsevier, vol. 173(C), pages 111-123.
    20. 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.

    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:rensus:v:162:y:2022:i:c:s1364032122002969. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.