IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v49y2018i12p2507-2524.html
   My bibliography  Save this article

𝕃1 adaptive networked controller for islanded distributed generation systems in a microgrid

Author

Listed:
  • Nezar M. Alyazidi
  • Magdi S. Mahmoud

Abstract

In this paper, we implement an output-feedback $ \mathfrak{L}_{1} $ L1 adaptive controller for islanded distributed generation systems (DGs) with communication, load and generation constraints. The $ \mathfrak{L}_{1} $ L1 adaptive controller is introduced to deal with nonlinearities of dynamical systems and unknown constraints. It primarily consists of a predictor, an adaptive law, and a control law. Herein, the controller can sustain desired performance and the robustness, in which the control law loop contains a low pass filter that sustain a rapid adaptation rate without fluctuations. The critical challenge into a standalone microgrid is to coordinate the necessitate load power with the distributed generations production in the presence of load/generation fluctuations. The coordinated controller is implemented to undertake the conflicts, and to enhance the performance, and to minimise the control cost by coordinate the requirements between decentralised controllers. The proposed controller is worthy for ensuring the network stability of DGs in a microgrid environment in the presence of uncertainties and transmission time delays. A typical simulation example is presented to confirm the effectiveness of the proposed design procedure.

Suggested Citation

  • Nezar M. Alyazidi & Magdi S. Mahmoud, 2018. "𝕃1 adaptive networked controller for islanded distributed generation systems in a microgrid," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(12), pages 2507-2524, September.
  • Handle: RePEc:taf:tsysxx:v:49:y:2018:i:12:p:2507-2524
    DOI: 10.1080/00207721.2018.1487093
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2018.1487093
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207721.2018.1487093?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tsysxx:v:49:y:2018:i:12:p:2507-2524. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    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.