IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i14p2681-d247811.html
   My bibliography  Save this article

Adaptive Command-Filtered Backstepping Control for Virtual Synchronous Generators

Author

Listed:
  • Chengshun Yang

    (Nanjing Institute of Technology, School of Electric Power Engineering, Nanjing 211167, China)

  • Fan Yang

    (Nanjing Institute of Technology, School of Electric Power Engineering, Nanjing 211167, China)

  • Dezhi Xu

    (School of IoT Engineering, Jiangnan University, Wuxi 214122, China)

  • Xiaoning Huang

    (Nanjing Institute of Technology, School of Electric Power Engineering, Nanjing 211167, China)

  • Dongdong Zhang

    (Nanjing Institute of Technology, School of Electric Power Engineering, Nanjing 211167, China)

Abstract

Distributed energy sources are usually interfaced to the grid using power electronic converters, and lack of inertia in inverter dominated microgrids can affect the system stability. This paper presents a new method for virtual synchronous generator (VSG) control in order to solve the low system inertia and support the grid frequency problem. In this paper, the VSG based on electromagnetic transient characteristics is improved and an adaptive command filter back-stepping controller is designed. Firstly, the rotor swing equation and power part are modeled to complete the controller design for achieving system stability in the islanded, grid-connected and transition modes. In addition, a limited-amplitude command filter is used to deal with computational complexity and nonlinear saturation problems in the design process. Secondly, projection operator, and adaptive inertia and damping control are introduced to reduce the modeling error and disturbance caused by changing parameters. This ensures the boundedness of the estimated value and further improves the frequency response, especially in the transition mode. Finally, simulation results show that the proposed controller is more effective than the traditional control method for achieving power stability and frequency improvement.

Suggested Citation

  • Chengshun Yang & Fan Yang & Dezhi Xu & Xiaoning Huang & Dongdong Zhang, 2019. "Adaptive Command-Filtered Backstepping Control for Virtual Synchronous Generators," Energies, MDPI, vol. 12(14), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2681-:d:247811
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/14/2681/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/14/2681/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ting Yang & Yajian Zhang & Zhaoxia Wang & Haibo Pen, 2018. "Secondary Frequency Stochastic Optimal Control in Independent Microgrids with Virtual Synchronous Generator-Controlled Energy Storage Systems," Energies, MDPI, vol. 11(9), pages 1-14, September.
    2. Di Hu & Ming Ding & Lei Sun & Jingjing Zhang, 2019. "Planning of High Renewable-Penetrated Distribution Systems Considering Complementarity and Cluster Partitioning," Energies, MDPI, vol. 12(11), pages 1-22, May.
    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. Chih-Hong Lin, 2020. "Permanent-Magnet Synchronous Motor Drive System Using Backstepping Control with Three Adaptive Rules and Revised Recurring Sieved Pollaczek Polynomials Neural Network with Reformed Grey Wolf Optimizat," Energies, MDPI, vol. 13(22), pages 1-33, November.
    2. Der-Fa Chen & Yi-Cheng Shih & Shih-Cheng Li & Chin-Tung Chen & Jung-Chu Ting, 2020. "Permanent-Magnet SLM Drive System Using AMRRSPNNB Control System with DGWO," Energies, MDPI, vol. 13(11), pages 1-25, June.
    3. Chih-Hong Lin, 2020. "A Rectified Reiterative Sieved-Pollaczek Polynomials Neural Network Backstepping Control with Improved Fish School Search for Motor Drive System," Mathematics, MDPI, vol. 8(10), pages 1-34, 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. Xinghua Wang & Fucheng Zhong & Yilin Xu & Xixian Liu & Zezhong Li & Jianan Liu & Zhuoli Zhao, 2023. "Extraction and Joint Method of PV–Load Typical Scenes Considering Temporal and Spatial Distribution Characteristics," Energies, MDPI, vol. 16(18), pages 1-19, September.
    2. Gholam Ali Alizadeh & Tohid Rahimi & Mohsen Hasan Babayi Nozadian & Sanjeevikumar Padmanaban & Zbigniew Leonowicz, 2019. "Improving Microgrid Frequency Regulation Based on the Virtual Inertia Concept while Considering Communication System Delay," Energies, MDPI, vol. 12(10), pages 1-15, May.
    3. Eng Tseng Lau & Kok Keong Chai & Yue Chen & Jonathan Loo, 2018. "Efficient Economic and Resilience-Based Optimization for Disaster Recovery Management of Critical Infrastructures," Energies, MDPI, vol. 11(12), pages 1-20, December.
    4. Min-Rong Chen & Guo-Qiang Zeng & Yu-Xing Dai & Kang-Di Lu & Da-Qiang Bi, 2018. "Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid," Energies, MDPI, vol. 12(1), pages 1-21, December.
    5. Latif, Abdul & Hussain, S.M. Suhail & Das, Dulal Chandra & Ustun, Taha Selim, 2020. "State-of-the-art of controllers and soft computing techniques for regulated load frequency management of single/multi-area traditional and renewable energy based power systems," Applied Energy, Elsevier, vol. 266(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:12:y:2019:i:14:p:2681-:d:247811. 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.