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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
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    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. 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.
    3. 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.
    4. 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).
    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.
    6. 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.
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