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Comparison between synthetic inertia and fast frequency containment control based on single phase EVs in a microgrid

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  • Rezkalla, Michel
  • Zecchino, Antonio
  • Martinenas, Sergejus
  • Prostejovsky, Alexander M.
  • Marinelli, Mattia

Abstract

The increasing share of distributed and inertia-less resources entails an upsurge in balancing and system stabilisation services. In particular, the displacement of conventional generation reduces the available rotational inertia in the power system, leading to high interest in synthetic inertia solutions. The objective of this paper is twofold: first, it aims to implement and validate fast frequency control and synthetic (virtual) inertia control, employing single phase electric vehicles as flexibility resources. Second, it proposes a trade-off analysis between the two controllers. The interdependency between frequency containment and synthetic inertia control on the transient frequency variation is shown analytically. The capabilities and limits of series produced EVs in providing such services are investigated, first on a simulation based approach and subsequently by using real hardware. The results show that fast frequency control can improve the transient frequency behaviour. However, both on the simulation and on the experimental level, the implementation of synthetic inertia control is more challenging. In fact, due its derivative nature and the system dynamics, its performance is limited. Furthermore, the crucial importance of the EVs’ response time for both controllers is highlighted.

Suggested Citation

  • Rezkalla, Michel & Zecchino, Antonio & Martinenas, Sergejus & Prostejovsky, Alexander M. & Marinelli, Mattia, 2018. "Comparison between synthetic inertia and fast frequency containment control based on single phase EVs in a microgrid," Applied Energy, Elsevier, vol. 210(C), pages 764-775.
    • Handle: RePEc:eee:appene:v:210:y:2018:i:c:p:764-775
    DOI: 10.1016/j.apenergy.2017.06.051
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    References listed on IDEAS

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    1. Tielens, Pieter & Van Hertem, Dirk, 2016. "The relevance of inertia in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 999-1009.
    2. Foley, Aoife & Tyther, Barry & Calnan, Patrick & Ó Gallachóir, Brian, 2013. "Impacts of Electric Vehicle charging under electricity market operations," Applied Energy, Elsevier, vol. 101(C), pages 93-102.
    3. Schuller, Alexander & Flath, Christoph M. & Gottwalt, Sebastian, 2015. "Quantifying load flexibility of electric vehicles for renewable energy integration," Applied Energy, Elsevier, vol. 151(C), pages 335-344.
    4. Hedegaard, Karsten & Ravn, Hans & Juul, Nina & Meibom, Peter, 2012. "Effects of electric vehicles on power systems in Northern Europe," Energy, Elsevier, vol. 48(1), pages 356-368.
    5. Mu, Yunfei & Wu, Jianzhong & Jenkins, Nick & Jia, Hongjie & Wang, Chengshan, 2014. "A Spatial–Temporal model for grid impact analysis of plug-in electric vehicles," Applied Energy, Elsevier, vol. 114(C), pages 456-465.
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    Citations

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    Cited by:

    1. Jürgen Marchgraber & Christian Alács & Yi Guo & Wolfgang Gawlik & Adolfo Anta & Alexander Stimmer & Martin Lenz & Manuel Froschauer & Michaela Leonhardt, 2020. "Comparison of Control Strategies to Realize Synthetic Inertia in Converters," Energies, MDPI, vol. 13(13), pages 1-21, July.
    2. Dario Garozzo & Giuseppe Marco Tina, 2020. "Evaluation of the Effective Active Power Reserve for Fast Frequency Response of PV with BESS Inverters Considering Reactive Power Control," Energies, MDPI, vol. 13(13), pages 1-16, July.
    3. Evgeny Nefedov & Seppo Sierla & Valeriy Vyatkin, 2018. "Internet of Energy Approach for Sustainable Use of Electric Vehicles as Energy Storage of Prosumer Buildings," Energies, MDPI, vol. 11(8), pages 1-18, August.
    4. Sevdari, Kristian & Calearo, Lisa & Andersen, Peter Bach & Marinelli, Mattia, 2022. "Ancillary services and electric vehicles: An overview from charging clusters and chargers technology perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    5. Erbaş, Mehmet & Kabak, Mehmet & Özceylan, Eren & Çetinkaya, Cihan, 2018. "Optimal siting of electric vehicle charging stations: A GIS-based fuzzy Multi-Criteria Decision Analysis," Energy, Elsevier, vol. 163(C), pages 1017-1031.
    6. Attya, A.B. & Anaya-Lara, O. & Leithead, W.E., 2018. "Novel concept of renewables association with synchronous generation for enhancing the provision of ancillary services," Applied Energy, Elsevier, vol. 229(C), pages 1035-1047.
    7. Ruben Garruto & Michela Longo & Wahiba Yaïci & Federica Foiadelli, 2020. "Connecting Parking Facilities to the Electric Grid: A Vehicle-to-Grid Feasibility Study in a Railway Station’s Car Park," Energies, MDPI, vol. 13(12), pages 1-23, June.
    8. Qiu, Dawei & Wang, Yi & Sun, Mingyang & Strbac, Goran, 2022. "Multi-service provision for electric vehicles in power-transportation networks towards a low-carbon transition: A hierarchical and hybrid multi-agent reinforcement learning approach," Applied Energy, Elsevier, vol. 313(C).
    9. Sohail Khan & Benoit Bletterie & Adolfo Anta & Wolfgang Gawlik, 2018. "On Small Signal Frequency Stability under Virtual Inertia and the Role of PLLs," Energies, MDPI, vol. 11(9), pages 1-18, September.

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