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Techno Economic Analysis of Electric Vehicle Grid Integration Aimed to Provide Network Flexibility Services in Italian Regulatory Framework

Author

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  • Daniele Menniti

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy)

  • Anna Pinnarelli

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy)

  • Nicola Sorrentino

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy)

  • Pasquale Vizza

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy)

  • Giovanni Brusco

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy)

  • Giuseppe Barone

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy)

  • Gianluca Marano

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy)

Abstract

The recent forecasts regarding the penetration of electric vehicles (EVs) in the transport market and their impact on national electricity distribution grids has presented new challenges in the fields of both of application and research. In this context, vehicle-to-grid (V2G) technology presents itself as an extremely valid solution in terms of application of the “demand side flexibility” paradigm. In this context, the aim of the paper is to analyze from a technical and economical point of view the use of EVs as new flexibility resources to provide network flexibility services in an Italian framework. Within this scope, a methodology for evaluating the flexibility service that a single EV or an EV fleet can offer, and therefore for estimating the EV storage system charge and discharge profile and determining its economic benefit, is proposed. Some numerical results and observations are reported to highlight possible incentive mechanisms for motivating EV end-users to offer flexibility services.

Suggested Citation

  • Daniele Menniti & Anna Pinnarelli & Nicola Sorrentino & Pasquale Vizza & Giovanni Brusco & Giuseppe Barone & Gianluca Marano, 2022. "Techno Economic Analysis of Electric Vehicle Grid Integration Aimed to Provide Network Flexibility Services in Italian Regulatory Framework," Energies, MDPI, vol. 15(7), pages 1-34, March.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2355-:d:778123
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    References listed on IDEAS

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    1. Muhammad Huda & Tokimatsu Koji & Muhammad Aziz, 2020. "Techno Economic Analysis of Vehicle to Grid (V2G) Integration as Distributed Energy Resources in Indonesia Power System," Energies, MDPI, vol. 13(5), pages 1-16, March.
    2. Sovacool, Benjamin K. & Kester, Johannes & Noel, Lance & Zarazua de Rubens, Gerardo, 2020. "Actors, business models, and innovation activity systems for vehicle-to-grid (V2G) technology: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    3. Novosel, T. & Perković, L. & Ban, M. & Keko, H. & Pukšec, T. & Krajačić, G. & Duić, N., 2015. "Agent based modelling and energy planning – Utilization of MATSim for transport energy demand modelling," Energy, Elsevier, vol. 92(P3), pages 466-475.
    4. Sai Sudharshan Ravi & Muhammad Aziz, 2022. "Utilization of Electric Vehicles for Vehicle-to-Grid Services: Progress and Perspectives," Energies, MDPI, vol. 15(2), pages 1-27, January.
    5. Bruno Canizes & João Soares & Angelo Costa & Tiago Pinto & Fernando Lezama & Paulo Novais & Zita Vale, 2019. "Electric Vehicles’ User Charging Behaviour Simulator for a Smart City," Energies, MDPI, vol. 12(8), pages 1-20, April.
    6. Gough, Rebecca & Dickerson, Charles & Rowley, Paul & Walsh, Chris, 2017. "Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage," Applied Energy, Elsevier, vol. 192(C), pages 12-23.
    7. Das, Ridoy & Wang, Yue & Putrus, Ghanim & Kotter, Richard & Marzband, Mousa & Herteleer, Bert & Warmerdam, Jos, 2020. "Multi-objective techno-economic-environmental optimisation of electric vehicle for energy services," Applied Energy, Elsevier, vol. 257(C).
    8. Cardoso, G. & Stadler, M. & Bozchalui, M.C. & Sharma, R. & Marnay, C. & Barbosa-Póvoa, A. & Ferrão, P., 2014. "Optimal investment and scheduling of distributed energy resources with uncertainty in electric vehicle driving schedules," Energy, Elsevier, vol. 64(C), pages 17-30.
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    Cited by:

    1. Giovanni Brusco & Daniele Menniti & Anna Pinnarelli & Nicola Sorrentino & Pasquale Vizza, 2023. "Power Cloud Framework for Prosumer Aggregation to Unlock End-User Flexibility," Energies, MDPI, vol. 16(20), pages 1-17, October.
    2. Patrick Dossow & Maximilian Hampel, 2023. "Synergies of Electric Vehicle Multi-Use: Analyzing the Implementation Effort for Use Case Combinations in Smart E-Mobility," Energies, MDPI, vol. 16(5), pages 1-35, March.

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