IDEAS home Printed from https://ideas.repec.org/a/ids/ijgeni/v44y2022i5-6p454-470.html
   My bibliography  Save this article

Optimisation of frequency response parameters of new energy distribution network based on linear correction

Author

Listed:
  • Xin Mao
  • Yufan Rao
  • Min Gong
  • Xuemin Song
  • Lixing Zhou

Abstract

In order to overcome the problems of high response adjustment rate and low optimisation efficiency existing in the existing frequency response parameter optimisation methods of distribution network, a new optimisation method for frequency response parameter of new energy distribution network based on linear correction is proposed. Firstly, the frequency response demand of new energy distribution network is analysed, and the frequency regulation index of PV and wind power is obtained. Combined with linear correction algorithm, the frequency response parameter model of new energy distribution network is constructed. The fuzzy control theory and genetic algorithm are combined to solve the model to effectively optimise the frequency response parameters of new energy distribution network. Simulation results show that the proposed method cannot only effectively reduce the frequency response adjustment rate of distribution network, but also effectively reduce the optimisation time and cost.

Suggested Citation

  • Xin Mao & Yufan Rao & Min Gong & Xuemin Song & Lixing Zhou, 2022. "Optimisation of frequency response parameters of new energy distribution network based on linear correction," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 44(5/6), pages 454-470.
    • Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:454-470
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=125404
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    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:ids:ijgeni:v:44:y:2022:i:5/6:p:454-470. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=13 .

    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.