IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2022i1p421-d1019607.html
   My bibliography  Save this article

Accurate Peer-to-Peer Hierarchical Control Method for Hybrid DC Microgrid Clusters

Author

Listed:
  • Ensheng Zhao

    (School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Yang Han

    (School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Hao Zeng

    (School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Luqiao Li

    (China Academy of Engineering Physics, Mianyang 624900, China)

  • Ping Yang

    (School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Congling Wang

    (School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Amr S. Zalhaf

    (School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
    Electrical Power and Machines Engineering Department, Tanta University, Tanta 31511, Egypt)

Abstract

Hybrid DC microgrid clusters contain various types of converters such as BOOST, BUCK, and bidirectional DC/DC converters, making the control strategy complex and difficult to achieve plug-and-play. The common master–slave hierarchical control strategy makes it difficult to achieve accurate and stable system control. This paper proposes an accurate peer-to-peer hierarchical control method for the hybrid DC microgrid cluster, and the working principle of this hierarchical control method is analyzed in detail. The microgrid cluster consists of three sub-microgrids, where sub-microgrid A consists of three BUCK converters, sub-microgrid B consists of three BOOST converters, and sub-microgrid C consists of two bidirectional DC/DC converters. According to all possible operations of various sub-microgrids in the microgrid cluster, the top-, mid-, and bottom-level controls are designed to solve the coordination control problem among different types of sub-microgrids. In this paper, a hybrid microgrid cluster simulation model is built in the PLECS simulation environment, and an experimental hardware platform is designed. The simulation and experiment results verified the accuracy of the proposed control strategy and its fast plug-and-play regulation ability for the system.

Suggested Citation

  • Ensheng Zhao & Yang Han & Hao Zeng & Luqiao Li & Ping Yang & Congling Wang & Amr S. Zalhaf, 2022. "Accurate Peer-to-Peer Hierarchical Control Method for Hybrid DC Microgrid Clusters," Energies, MDPI, vol. 16(1), pages 1-27, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:421-:d:1019607
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/1/421/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/1/421/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Junjie Ma & Xudong Wang & Siyan Zhang & Hanying Gao, 2021. "Distributed Finite-Time Secondary Frequency and Voltage Restoration Control Scheme of an Islanded AC Microgrid," Energies, MDPI, vol. 14(19), pages 1-20, October.
    2. Li, Xiangke & Dong, Chaoyu & Jiang, Wentao & Wu, Xiaohua, 2021. "An improved coordination control for a novel hybrid AC/DC microgrid architecture with combined energy storage system," Applied Energy, Elsevier, vol. 292(C).
    3. Dong, Chaoyu & Gao, Qingbin & Xiao, Qian & Yu, Xiaodan & Pekař, Libor & Jia, Hongjie, 2018. "Time-delay stability switching boundary determination for DC microgrid clusters with the distributed control framework," Applied Energy, Elsevier, vol. 228(C), pages 189-204.
    4. Siyuan Liu & Xiaona Liu & Shaojie Jiang & Zengnan Zhao & Ning Wang & Xiaoyu Liang & Minghui Zhang & Lihua Wang, 2022. "Application of an Improved STSMC Method to the Bidirectional DC–DC Converter in Photovoltaic DC Microgrid," Energies, MDPI, vol. 15(5), pages 1-16, February.
    5. dos Santos Neto, Pedro J. & Barros, Tárcio A.S. & Silveira, Joao P.C. & Ruppert Filho, Ernesto & Vasquez, Juan C. & Guerrero, Josep M., 2020. "Power management techniques for grid-connected DC microgrids: A comparative evaluation," Applied Energy, Elsevier, vol. 269(C).
    6. Wenguo Li & Mingmin Zhang & Yaqi Deng, 2022. "Consensus-Based Distributed Secondary Frequency Control Method for AC Microgrid Using ADRC Technique," Energies, MDPI, vol. 15(9), pages 1-19, April.
    7. Md Masud Rana & Mohamed Atef & Md Rasel Sarkar & Moslem Uddin & GM Shafiullah, 2022. "A Review on Peak Load Shaving in Microgrid—Potential Benefits, Challenges, and Future Trend," Energies, MDPI, vol. 15(6), pages 1-17, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kafeel Ahmed & Irfan Hussain & Mehdi Seyedmahmoudian & Alex Stojcevski & Saad Mekhilef, 2023. "Voltage Stability and Power Sharing Control of Distributed Generation Units in DC Microgrids," Energies, MDPI, vol. 16(20), pages 1-17, October.

    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. Armghan, Hammad & Xu, Yinliang & Sun, Hongbin & Ali, Naghmash & Liu, Jiajin, 2024. "Event-triggered multi-time scale control and low carbon operation for electric-hydrogen DC microgrid," Applied Energy, Elsevier, vol. 355(C).
    2. Abulanwar, Sayed & Ghanem, Abdelhady & Rizk, Mohammad E.M. & Hu, Weihao, 2021. "Adaptive synergistic control strategy for a hybrid AC/DC microgrid during normal operation and contingencies," Applied Energy, Elsevier, vol. 304(C).
    3. Fouad Boutros & Moustapha Doumiati & Jean-Christophe Olivier & Imad Mougharbel & Hadi Kanaan, 2024. "Optimal Placement of Multiple Sources in a Mesh-Type DC Microgrid Using Dijkstra’s Algorithm," Energies, MDPI, vol. 17(14), pages 1-18, July.
    4. Hallemans, L. & Ravyts, S. & Govaerts, G. & Fekriasl, S. & Van Tichelen, P. & Driesen, J., 2022. "A stepwise methodology for the design and evaluation of protection strategies in LVDC microgrids," Applied Energy, Elsevier, vol. 310(C).
    5. Wang He & Min Liu & Chaowen Zuo & Kai Wang, 2023. "Massive Multi-Source Joint Outbound and Benefit Distribution Model Based on Cooperative Game," Energies, MDPI, vol. 16(18), pages 1-19, September.
    6. Harrold, Daniel J.B. & Cao, Jun & Fan, Zhong, 2022. "Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning," Applied Energy, Elsevier, vol. 318(C).
    7. Alberto Arellanes & Ciro Nuñez & Nancy Visairo & Andres A. Valdez-Fernandez, 2022. "An Improvement of Holistic Control Tuning for Reducing Energy Consumption in Seamless Transitions for a BESS Grid-Connected Converter," Energies, MDPI, vol. 15(21), pages 1-23, October.
    8. Yu, Hang & Shang, Yitong & Niu, Songyan & Cheng, Chong & Shao, Ziyun & Jian, Linni, 2022. "Towards energy-efficient and cost-effective DC nanaogrid: A novel pseudo hierarchical architecture incorporating V2G technology for both autonomous coordination and regulated power dispatching," Applied Energy, Elsevier, vol. 313(C).
    9. O., Yugeswar Reddy & J., Jithendranath & Chakraborty, Ajoy Kumar & Guerrero, Josep M., 2022. "Stochastic optimal power flow in islanded DC microgrids with correlated load and solar PV uncertainties," Applied Energy, Elsevier, vol. 307(C).
    10. Rasool Kahani & Mohsin Jamil & M. Tariq Iqbal, 2022. "Direct Model Reference Adaptive Control of a Boost Converter for Voltage Regulation in Microgrids," Energies, MDPI, vol. 15(14), pages 1-19, July.
    11. Hussein A.Z. AL-bonsrulah & Mohammed J. Alshukri & Lama M. Mikhaeel & Noor N. AL-sawaf & Kefif Nesrine & M.V. Reddy & Karim Zaghib, 2021. "Design and Simulation Studies of Hybrid Power Systems Based on Photovoltaic, Wind, Electrolyzer, and PEM Fuel Cells," Energies, MDPI, vol. 14(9), pages 1-25, May.
    12. Pablo Carrasco Ortega & Pablo Durán Gómez & Julio César Mérida Sánchez & Fernando Echevarría Camarero & Ángel Á. Pardiñas, 2023. "Battery Energy Storage Systems for the New Electricity Market Landscape: Modeling, State Diagnostics, Management, and Viability—A Review," Energies, MDPI, vol. 16(17), pages 1-51, August.
    13. Bouzid, Allal El Moubarek & Chaoui, Hicham & Zerrougui, Mohamed & Ben Elghali, Seifeddine & Benbouzid, Mohamed, 2021. "Robust control based on linear matrix inequalities criterion of single phase distributed electrical energy systems operating in islanded and grid-connected modes," Applied Energy, Elsevier, vol. 292(C).
    14. dos Santos Neto, Pedro J. & Barros, Tárcio A.S. & Silveira, Joao P.C. & Ruppert Filho, Ernesto & Vasquez, Juan C. & Guerrero, Josep M., 2020. "Power management techniques for grid-connected DC microgrids: A comparative evaluation," Applied Energy, Elsevier, vol. 269(C).
    15. Ferahtia, Seydali & Rezk, Hegazy & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal techno-economic energy management strategy for building’s microgrids based bald eagle search optimization algorithm," Applied Energy, Elsevier, vol. 306(PB).
    16. Tri Ardriani & Pekik Argo Dahono & Arwindra Rizqiawan & Erna Garnia & Pungky Dwi Sastya & Ahmad Husnan Arofat & Muhammad Ridwan, 2021. "A DC Microgrid System for Powering Remote Areas," Energies, MDPI, vol. 14(2), pages 1-15, January.
    17. Deakin, Matthew & Sarantakos, Ilias & Greenwood, David & Bialek, Janusz & Taylor, Phil C. & Walker, Sara, 2023. "Comparative analysis of services from soft open points using cost–benefit analysis," Applied Energy, Elsevier, vol. 333(C).
    18. Florian Klausmann & Anna-Lena Klingler, 2023. "Adaptive Control Strategy for Stationary Electric Battery Storage Systems with Reliable Peak Load Limitation at Maximum Self-Consumption of Locally Generated Energy," Energies, MDPI, vol. 16(9), pages 1-19, May.
    19. Albert Sawiński & Piotr Chudzik & Karol Tatar, 2024. "SMC Algorithms in T-Type Bidirectional Power Grid Converter," Energies, MDPI, vol. 17(12), pages 1-19, June.
    20. Wang, Yijian & Cui, Yang & Li, Yang & Xu, Yang, 2023. "Collaborative optimization of multi-microgrids system with shared energy storage based on multi-agent stochastic game and reinforcement learning," Energy, Elsevier, vol. 280(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:16:y:2022:i:1:p:421-:d:1019607. 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.