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Optimal Control of Plug-In Electric Vehicles Charging for Composition of Frequency Regulation Services

Author

Listed:
  • Roberto Germanà

    (Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy)

  • Francesco Liberati

    (Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy)

  • Emanuele De Santis

    (Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy)

  • Alessandro Giuseppi

    (Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy)

  • Francesco Delli Priscoli

    (Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy)

  • Alessandro Di Giorgio

    (Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy)

Abstract

This paper presents a novel control system for the participation of plug-in electric vehicles (PEVs) in the provisioning of ancillary services for frequency regulation, in a way that is transparent to the driver and harmonized with the smart charging service requirements. Given a power-frequency droop curve, which specifies how the set of PEVs collectively participate to the provisioning of the frequency regulation service (we call this curve a “global” droop curve), we propose an algorithm to compute “local” droop curves (one for each PEV), which are optimized according to the current status of the PEV and the current progress of the smart recharging session. Once aggregated, the local droop curves match the global one (so that the PEVs contribute as expected to the provisioning of the ancillary service). One innovative aspect of the proposed algorithm is that it is specifically designed to be interoperable with the algorithms that control the PEV recharging process; hence, it is transparent to the PEV drivers. Simulation results are presented to validate the proposed solution.

Suggested Citation

  • Roberto Germanà & Francesco Liberati & Emanuele De Santis & Alessandro Giuseppi & Francesco Delli Priscoli & Alessandro Di Giorgio, 2021. "Optimal Control of Plug-In Electric Vehicles Charging for Composition of Frequency Regulation Services," Energies, MDPI, vol. 14(23), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:7879-:d:686762
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    References listed on IDEAS

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    1. Jia, Hongjie & Li, Xiaomeng & Mu, Yunfei & Xu, Chen & Jiang, Yilang & Yu, Xiaodan & Wu, Jianzhong & Dong, Chaoyu, 2018. "Coordinated control for EV aggregators and power plants in frequency regulation considering time-varying delays," Applied Energy, Elsevier, vol. 210(C), pages 1363-1376.
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    Cited by:

    1. Ana Pavlićević & Saša Mujović, 2022. "Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses," Energies, MDPI, vol. 15(19), pages 1-24, September.
    2. Yuxuan Wang & Bingxu Zhang & Chenyang Li & Yongzhang Huang, 2022. "Collaborative Robust Optimization Strategy of Electric Vehicles and Other Distributed Energy Considering Load Flexibility," Energies, MDPI, vol. 15(8), pages 1-22, April.

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