IDEAS home Printed from https://ideas.repec.org/a/ids/ijgeni/v47y2025i4-5p452-465.html
   My bibliography  Save this article

Collaborative planning method for integrated energy system based on improved compressed sensing algorithm

Author

Listed:
  • Yan Li
  • Xiaojun Zhu
  • Qingshan Wang
  • Qiong Wang
  • Na Li
  • Yinzhe Xie
  • Zhu Chen

Abstract

Aiming at the problems of high-energy cost, high-energy consumption and environmental pollution in existing methods, a collaborative planning method for integrated energy systems based on improved compressed sensing algorithm is proposed. Build a comprehensive energy system architecture that includes modules for energy production, storage and conversion, transmission and distribution, consumption and management. Establish a collaborative planning mathematical model based on the characteristics of the architecture, set three objective functions: total energy consumption, total cost and total pollutant emissions, and set corresponding energy consumption, cost and environmental protection constraints. The improved compressed sensing algorithm is used for the integrated energy system collaborative planning, and the optimal solution is output, which is the optimal integrated energy system collaborative planning scheme. The experimental results show that the proposed method effectively reduces energy costs and energy consumption, and significantly reduces carbon dioxide emissions, indicating that the proposed method has practical value.

Suggested Citation

  • Yan Li & Xiaojun Zhu & Qingshan Wang & Qiong Wang & Na Li & Yinzhe Xie & Zhu Chen, 2025. "Collaborative planning method for integrated energy system based on improved compressed sensing algorithm," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 47(4/5), pages 452-465.
  • Handle: RePEc:ids:ijgeni:v:47:y:2025:i:4/5:p:452-465
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=147236
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:ids:ijgeni:v:47:y:2025:i:4/5:p:452-465. 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.