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Electric vehicle based smart e-mobility system – Definition and comparison to the existing concept

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  • Pavić, Ivan
  • Pandžić, Hrvoje
  • Capuder, Tomislav

Abstract

The existing models designed to reap the benefits of electric vehicles’ flexibility in the literature almost exclusively identify charging stations as active players exploiting this flexibility. Such stations are seen as static loads able to provide flexibility only when electric vehicles are connected to them. This standpoint, however, suffers from two major issues. First, the charging stations need to anticipate important parameters of the incoming vehicles, e.g. time of arrival/departure, state-of-energy at arrival/departure. Second, it interacts with vehicles only when connected to a specific charging station, thus overlooking the arbitrage opportunities when they are connected to other stations. This conventional way of addressing the electric vehicles is referred to as charging station-based e-mobility system. A new viewpoint is presented in this paper, where electric vehicles are observed as dynamic movable storage that can provide flexibility at any charging station. The paper defines both the existing system, where the flexibility is viewed from the standpoint of charging stations, and the proposed one, where the flexibility is viewed from the vehicles’ standpoint. The both concepts are mathematically formulated as linear optimization programs and run over a simple case study to numerically evaluate the differences. Each of the four issues identified are individually examined and omission of corresponding constraints is analysed and quantified. The main result is that the proposed system yields better results for the vehicle owners.

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  • Pavić, Ivan & Pandžić, Hrvoje & Capuder, Tomislav, 2020. "Electric vehicle based smart e-mobility system – Definition and comparison to the existing concept," Applied Energy, Elsevier, vol. 272(C).
  • Handle: RePEc:eee:appene:v:272:y:2020:i:c:s0306261920306656
    DOI: 10.1016/j.apenergy.2020.115153
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    References listed on IDEAS

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    1. Matteo Muratori, 2018. "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," Nature Energy, Nature, vol. 3(3), pages 193-201, March.
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    5. Pavić, Ivan & Capuder, Tomislav & Kuzle, Igor, 2016. "Low carbon technologies as providers of operational flexibility in future power systems," Applied Energy, Elsevier, vol. 168(C), pages 724-738.
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    Cited by:

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    2. Armando Cartenì & Ilaria Henke & Clorinda Molitierno & Luigi Di Francesco, 2020. "Strong Sustainability in Public Transport Policies: An e-Mobility Bus Fleet Application in Sorrento Peninsula (Italy)," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    3. Hassam ur Rehman & Jan Diriken & Ala Hasan & Stijn Verbeke & Francesco Reda, 2021. "Energy and Emission Implications of Electric Vehicles Integration with Nearly and Net Zero Energy Buildings," Energies, MDPI, vol. 14(21), pages 1-30, October.
    4. Zhang, Yuanjian & Gao, Bingzhao & Jiang, Jingjing & Liu, Chengyuan & Zhao, Dezong & Zhou, Quan & Chen, Zheng & Lei, Zhenzhen, 2023. "Cooperative power management for range extended electric vehicle based on internet of vehicles," Energy, Elsevier, vol. 273(C).
    5. Molla Shahadat Hossain Lipu & Tahia F. Karim & Shaheer Ansari & Md. Sazal Miah & Md. Siddikur Rahman & Sheikh T. Meraj & Rajvikram Madurai Elavarasan & Raghavendra Rajan Vijayaraghavan, 2022. "Intelligent SOX Estimation for Automotive Battery Management Systems: State-of-the-Art Deep Learning Approaches, Open Issues, and Future Research Opportunities," Energies, MDPI, vol. 16(1), pages 1-31, December.
    6. Najafi, Arsalan & Jasiński, Michał & Leonowicz, Zbigniew, 2022. "A hybrid distributed framework for optimal coordination of electric vehicle aggregators problem," Energy, Elsevier, vol. 249(C).

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