IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i20p7213-d1265624.html
   My bibliography  Save this article

Electric Vehicle Fleet Management for a Prosumer Building with Renewable Generation

Author

Listed:
  • Matteo Fresia

    (Department of Electrical, Electronic, Telecommunication Engineering and Naval Architecture, University of Genoa, 16145 Genova, Italy)

  • Stefano Bracco

    (Department of Electrical, Electronic, Telecommunication Engineering and Naval Architecture, University of Genoa, 16145 Genova, Italy)

Abstract

The integration of renewable energy systems in buildings leads to a reduction in energy bills for end users and a reduction in the carbon footprint of such buildings, usually referred to as prosumers. In addition, the installation of charging points for the electric vehicles of people working or living in these buildings can further improve the energy efficiency of the whole system if innovative technologies, such as vehicle-to-building (V2B) technologies, are implemented. The aim of this paper is to present an Energy Management System (EMS) based on mathematical programming that has been developed to optimally manage a prosumer building equipped with photovoltaics, a micro wind turbine and several charging points for electric vehicles. Capabilities curves of renewable power plant inverters are modelled within the EMS, as well as the possibility to apply power curtailment and V2B. The use of V2B technology reduces the amount of electricity purchased from the public grid, while the use of smart inverters for the power plants allows zero reactive power to be drawn from the grid. Levelized cost of electricity (LCOE) is used to quantify curtailment costs, while penalties on reactive power absorption from the distribution network are evaluated in accordance with the current regulatory framework. Specifically, the model is applied to a prosumer building owned by the postal service in a large city in Italy. The paper reports the main results of the study and proposes a sensitivity analysis on the number of charging stations and vehicles, as well as on the consideration of different typical days characterized by different load and generation profiles. This paper also investigates how errors in forecasting energy production from renewable sources impact the optimal operation of the whole system.

Suggested Citation

  • Matteo Fresia & Stefano Bracco, 2023. "Electric Vehicle Fleet Management for a Prosumer Building with Renewable Generation," Energies, MDPI, vol. 16(20), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7213-:d:1265624
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/20/7213/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/20/7213/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Axel Gautier & Julien Jacqmin & Jean-Christophe Poudou, 2018. "The prosumers and the grid," Journal of Regulatory Economics, Springer, vol. 53(1), pages 100-126, February.
    2. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2018. "Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule," Applied Energy, Elsevier, vol. 210(C), pages 1188-1206.
    3. Rücker, Fabian & Schoeneberger, Ilka & Wilmschen, Till & Sperling, Dustin & Haberschusz, David & Figgener, Jan & Sauer, Dirk Uwe, 2022. "Self-sufficiency and charger constraints of prosumer households with vehicle-to-home strategies," Applied Energy, Elsevier, vol. 317(C).
    4. Meng, Jian & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qu, Bo, 2016. "Dynamic frequency response from electric vehicles considering travelling behavior in the Great Britain power system," Applied Energy, Elsevier, vol. 162(C), pages 966-979.
    5. Fiaschi, Daniele & Bandinelli, Romeo & Conti, Silvia, 2012. "A case study for energy issues of public buildings and utilities in a small municipality: Investigation of possible improvements and integration with renewables," Applied Energy, Elsevier, vol. 97(C), pages 101-114.
    Full references (including those not matched with items on IDEAS)

    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. Tao, Miaomiao, 2024. "Dynamics between electric vehicle uptake and green development: Understanding the role of local government competition," Transport Policy, Elsevier, vol. 146(C), pages 227-240.
    2. Ahmed S. Alahmed & Lang Tong, 2022. "Integrating Distributed Energy Resources: Optimal Prosumer Decisions and Impacts of Net Metering Tariffs," Papers 2204.06115, arXiv.org, revised May 2022.
    3. Àlex Alonso & Jordi de la Hoz & Helena Martín & Sergio Coronas & Pep Salas & José Matas, 2020. "A Comprehensive Model for the Design of a Microgrid under Regulatory Constraints Using Synthetical Data Generation and Stochastic Optimization," Energies, MDPI, vol. 13(21), pages 1-26, October.
    4. Giulietti, Monica & Le Coq, Chloé & Willems, Bert & Anaya, Karim, 2019. "Smart Consumers in the Internet of Energy : Flexibility Markets & Services from Distributed Energy Resources," Other publications TiSEM 2edb43b5-bbd6-487d-abdf-7, Tilburg University, School of Economics and Management.
    5. Cambini, Carlo & Soroush, Golnoush, 2019. "Designing grid tariffs in the presence of distributed generation," Utilities Policy, Elsevier, vol. 61(C).
    6. Syed Muhammad Ahsan & Hassan Abbas Khan & Sarmad Sohaib & Anas M. Hashmi, 2023. "Optimized Power Dispatch for Smart Building and Electric Vehicles with V2V, V2B and V2G Operations," Energies, MDPI, vol. 16(13), pages 1-15, June.
    7. Hafiz Abdul Muqeet & Rehan Liaqat & Mohsin Jamil & Asharf Ali Khan, 2023. "A State-of-the-Art Review of Smart Energy Systems and Their Management in a Smart Grid Environment," Energies, MDPI, vol. 16(1), pages 1-23, January.
    8. Niu, Jide & Li, Xiaoyuan & Tian, Zhe & Yang, Hongxing, 2024. "Uncertainty analysis of the electric vehicle potential for a household to enhance robustness in decision on the EV/V2H technologies," Applied Energy, Elsevier, vol. 365(C).
    9. Mohammed Abdullah H. Alshehri & Youguang Guo & Gang Lei, 2023. "Energy Management Strategies of Grid-Connected Microgrids under Different Reliability Conditions," Energies, MDPI, vol. 16(9), pages 1-22, May.
    10. Ali Darudi & Hannes Weigt, 2024. "Review and Assessment of Decarbonized Future Electricity Markets," Energies, MDPI, vol. 17(18), pages 1-38, September.
    11. Zhang, Tairan & Sobhani, Behrouz, 2023. "Optimal economic programming of an energy hub in the power system while taking into account the uncertainty of renewable resources, risk-taking and electric vehicles using a developed routing method," Energy, Elsevier, vol. 271(C).
    12. Sai Bravo & Carole Haritchabalet, 2023. "Prosumers: Grid Storage vs Small Fuel-Cell," Working papers of Transitions Energétiques et Environnementales (TREE) hal-04119625, HAL.
    13. Ibrahim Abada, Andreas Ehrenmann, and Xavier Lambin, 2020. "On the Viability of Energy Communities," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    14. Golpîra, Hêriş & Khan, Syed Abdul Rehman, 2019. "A multi-objective risk-based robust optimization approach to energy management in smart residential buildings under combined demand and supply uncertainty," Energy, Elsevier, vol. 170(C), pages 1113-1129.
    15. Muhssin, Mazin T. & Cipcigan, Liana M. & Sami, Saif Sabah & Obaid, Zeyad Assi, 2018. "Potential of demand side response aggregation for the stabilization of the grids frequency," Applied Energy, Elsevier, vol. 220(C), pages 643-656.
    16. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Xu, Xiandong & Yu, Xiaodan, 2016. "Optimal day-ahead scheduling of integrated urban energy systems," Applied Energy, Elsevier, vol. 180(C), pages 1-13.
    17. Raatikainen, Mika & Skön, Jukka-Pekka & Leiviskä, Kauko & Kolehmainen, Mikko, 2016. "Intelligent analysis of energy consumption in school buildings," Applied Energy, Elsevier, vol. 165(C), pages 416-429.
    18. Mousavizade, Mirsaeed & Bai, Feifei & Garmabdari, Rasoul & Sanjari, Mohammad & Taghizadeh, Foad & Mahmoudian, Ali & Lu, Junwei, 2023. "Adaptive control of V2Gs in islanded microgrids incorporating EV owner expectations," Applied Energy, Elsevier, vol. 341(C).
    19. De Groote, Olivier & Gautier, Axel & Verboven, Frank, 2024. "The political economy of financing climate policy — Evidence from the solar PV subsidy programs," Resource and Energy Economics, Elsevier, vol. 77(C).
    20. Jefimowski, Włodzimierz & Szeląg, Adam & Steczek, Marcin & Nikitenko, Anatolii, 2020. "Vanadium redox flow battery parameters optimization in a transportation microgrid: A case study," Energy, Elsevier, vol. 195(C).

    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:16:y:2023:i:20:p:7213-:d:1265624. 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.