IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i6p2295-d776201.html
   My bibliography  Save this article

Dual-Active-Bridge Model and Control for Supporting Fast Synthetic Inertial Action

Author

Listed:
  • Stefania Cuoghi

    (Department of Electrical, Electronic and Information Engineering, University of Bologna, 40136 Bologna, Italy)

  • Riccardo Mandrioli

    (Department of Electrical, Electronic and Information Engineering, University of Bologna, 40136 Bologna, Italy)

  • Lohith Kumar Pittala

    (Department of Electrical, Electronic and Information Engineering, University of Bologna, 40136 Bologna, Italy)

  • Vincenzo Cirimele

    (Department of Electrical, Electronic and Information Engineering, University of Bologna, 40136 Bologna, Italy)

  • Mattia Ricco

    (Department of Electrical, Electronic and Information Engineering, University of Bologna, 40136 Bologna, Italy)

Abstract

This article proposes a dual-active-bridge control to support the fast synthetic inertial action in DC microgrids. First of all, the selection of the isolated DC/DC converter to link an energy storage system with the DC bus in a microgrid is analyzed and the advantages of the dual-active-bridge converter controlled by a single-phase shift modulation justify its selection. An active front-end can be then adapted to connect the DC bus with an AC grid. Secondly, this paper presents the design of a discrete PI controller for supporting fast synthetic inertial action. In particular, a discrete dual-active-bridge model based on the transferred power between both converter bridges, which overcomes the approximations of the output current linearization model, is proposed. Moreover, the article introduces a novel equation set to directly and dynamically tune discrete PI parameters to fulfill the design frequency specifications based on the inversion formulae method. In this way, during the voltage/power transients on the DC bus, the controller actively responds and recovers those transients within a grid fundamental cycle. Since the developed set of control equations is very simple, it can be easily implemented by a discrete control algorithm, avoiding the use of offline trial and error procedures which may lead to system instability under large load variations. Finally, the proposed control system is evaluated and validated in PLECS simulations and hardware-in-the-loop tests.

Suggested Citation

  • Stefania Cuoghi & Riccardo Mandrioli & Lohith Kumar Pittala & Vincenzo Cirimele & Mattia Ricco, 2022. "Dual-Active-Bridge Model and Control for Supporting Fast Synthetic Inertial Action," Energies, MDPI, vol. 15(6), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2295-:d:776201
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/6/2295/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/6/2295/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Makolo, Peter & Zamora, Ramon & Lie, Tek-Tjing, 2021. "The role of inertia for grid flexibility under high penetration of variable renewables - A review of challenges and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    2. Ratnam Kamala Sarojini & Palanisamy Kaliannan & Yuvaraja Teekaraman & Srete Nikolovski & Hamid Reza Baghaee, 2021. "An Enhanced Emulated Inertia Control for Grid-Connected PV Systems with HESS in a Weak Grid," Energies, MDPI, vol. 14(6), pages 1-19, March.
    3. Stefania Cuoghi & Riccardo Mandrioli & Lorenzo Ntogramatzidis & Grandi Gabriele, 2020. "Multileg Interleaved Buck Converter for EV Charging: Discrete-Time Model and Direct Control Design," Energies, MDPI, vol. 13(2), pages 1-18, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Russeil, Valentin & Lo Seen, Danny & Broust, François & Bonin, Muriel & Praene, Jean-Philippe, 2023. "Food and electricity self-sufficiency trade-offs in Reunion Island: Modelling land-use change scenarios with stakeholders," Land Use Policy, Elsevier, vol. 132(C).
    2. Ratnam Kamala Sarojini & Kaliannan Palanisamy & Enrico De Tuglie, 2022. "A Fuzzy Logic-Based Emulated Inertia Control to a Supercapacitor System to Improve Inertia in a Low Inertia Grid with Renewables," Energies, MDPI, vol. 15(4), pages 1-23, February.
    3. Zhang, Tengxi & Xin, Li & Wang, Shunjiang & Guo, Ren & Wang, Wentao & Cui, Jia & Wang, Peng, 2024. "A novel approach of energy and reserve scheduling for hybrid power systems: Frequency security constraints," Applied Energy, Elsevier, vol. 361(C).
    4. Ruiz-García, A. & Tadeo, F. & Nuez, I., 2023. "Role of permeability coefficients in salinity gradient energy generation by PRO systems with spiral wound membrane modules," Renewable Energy, Elsevier, vol. 215(C).
    5. Uvini Perera & Amanullah Maung Than Oo & Ramon Zamora, 2022. "Sub Synchronous Oscillations under High Penetration of Renewables—A Review of Existing Monitoring and Damping Methods, Challenges, and Research Prospects," Energies, MDPI, vol. 15(22), pages 1-23, November.
    6. Abid, Md. Shadman & Ahshan, Razzaqul & Al Abri, Rashid & Al-Badi, Abdullah & Albadi, Mohammed, 2024. "Techno-economic and environmental assessment of renewable energy sources, virtual synchronous generators, and electric vehicle charging stations in microgrids," Applied Energy, Elsevier, vol. 353(PA).
    7. L., Lavanya & Swarup, K.S., 2024. "Inertia monitoring in power systems: Critical features, challenges, and framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    8. Barone, G. & Buonomano, A. & Forzano, C. & Palombo, A. & Russo, G., 2023. "The role of energy communities in electricity grid balancing: A flexible tool for smart grid power distribution optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    9. Asmamaw Sewnet & Baseem Khan & Issaias Gidey & Om Prakash Mahela & Adel El-Shahat & Almoataz Y. Abdelaziz, 2022. "Mitigating Generation Schedule Deviation of Wind Farm Using Battery Energy Storage System," Energies, MDPI, vol. 15(5), pages 1-26, February.
    10. Xiaolong Liu & Xinran Li & Ya Meng & Changqin Chen & Yang Yang, 2022. "Optimized wavelet packet analysis for photovoltaic wave power suppression [An enhanced emulated inertia control for grid-connected PV systems with HESS in a weak grid]," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 17, pages 90-96.
    11. Han, Kunlun & Yang, Kai & Yin, Linfei, 2022. "Lightweight actor-critic generative adversarial networks for real-time smart generation control of microgrids," Applied Energy, Elsevier, vol. 317(C).
    12. Wei Wang & Gaoshuai Shen & Run Min & Qiaoling Tong & Qiao Zhang & Zhenglin Liu, 2020. "State Switched Discrete-Time Model and Digital Predictive Voltage Programmed Control for Buck Converters," Energies, MDPI, vol. 13(13), pages 1-21, July.
    13. Li, Wei & Zhang, Lianjie & Klemeš, Jiří Jaromír & Wang, Qiuwang & Zeng, Min, 2022. "Thermochemical energy conversion behaviour in the corrugated heat storage unit with porous metal support," Energy, Elsevier, vol. 259(C).
    14. Armel Asongu Nkembi & Paolo Cova & Emilio Sacchi & Emanuele Coraggioso & Nicola Delmonte, 2023. "A Comprehensive Review of Power Converters for E-Mobility," Energies, MDPI, vol. 16(4), pages 1-28, February.
    15. Zhang, Mingze & Li, Weidong & Yu, Samson Shenglong & Wang, Haixia & Ba, Yu, 2024. "Optimal day-ahead large-scale battery dispatch model for multi-regulation participation considering full timescale uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    16. Stelios C. Dimoulias & Eleftherios O. Kontis & Grigoris K. Papagiannis, 2022. "Inertia Estimation of Synchronous Devices: Review of Available Techniques and Comparative Assessment of Conventional Measurement-Based Approaches," Energies, MDPI, vol. 15(20), pages 1-30, October.
    17. Salvatore Musumeci, 2023. "Energy Conversion Using Electronic Power Converters: Technologies and Applications," Energies, MDPI, vol. 16(8), pages 1-9, April.
    18. Yin, Linfei & Zheng, Da, 2024. "Decomposition prediction fractional-order PID reinforcement learning for short-term smart generation control of integrated energy systems," Applied Energy, Elsevier, vol. 355(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2295-:d:776201. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.