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An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †

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  • Shi You

    (Department of Electrical Engineering, Technical University of Denmark, Elektrovej 325, DK-2800 Kgs. Lyngby, Denmark)

  • Junjie Hu

    (Department of Electrical Engineering, Technical University of Denmark, Elektrovej 325, DK-2800 Kgs. Lyngby, Denmark)

  • Charalampos Ziras

    (Department of Electrical Engineering, Technical University of Denmark, Elektrovej 325, DK-2800 Kgs. Lyngby, Denmark)

Abstract

The design and implementation of management policies for plug-in electric vehicles (PEVs) need to be supported by a holistic understanding of the functional processes, their complex interactions, and their response to various changes. Models developed to represent different functional processes and systems are seen as useful tools to support the related studies for different stakeholders in a tangible way. This paper presents an overview of modeling approaches applied to support aggregation-based management and integration of PEVs from the perspective of fleet operators and grid operators, respectively. We start by explaining a structured modeling approach, i.e., a flexible combination of process models and system models, applied to different management and integration studies. A state-of-the-art overview of modeling approaches applied to represent several key processes, such as charging management, and key systems, such as the PEV fleet, is then presented, along with a detailed description of different approaches. Finally, we discuss several considerations that need to be well understood during the modeling process in order to assist modelers and model users in the appropriate decisions of using existing, or developing their own, solutions for further applications.

Suggested Citation

  • Shi You & Junjie Hu & Charalampos Ziras, 2016. "An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †," Energies, MDPI, vol. 9(11), pages 1-18, November.
  • Handle: RePEc:gam:jeners:v:9:y:2016:i:11:p:968-:d:83210
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    References listed on IDEAS

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    3. Tan, Kang Miao & Padmanaban, Sanjeevikumar & Yong, Jia Ying & Ramachandaramurthy, Vigna K., 2019. "A multi-control vehicle-to-grid charger with bi-directional active and reactive power capabilities for power grid support," Energy, Elsevier, vol. 171(C), pages 1150-1163.
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    5. Calum Strange & Rasheed Ibraheem & Gonçalo dos Reis, 2023. "Online Lifetime Prediction for Lithium-Ion Batteries with Cycle-by-Cycle Updates, Variance Reduction, and Model Ensembling," Energies, MDPI, vol. 16(7), pages 1-14, April.

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