IDEAS home Printed from https://ideas.repec.org/a/spr/snopef/v6y2025i3d10.1007_s43069-025-00494-1.html
   My bibliography  Save this article

Modelling and Optimal Utilisation of the Renewable Energy Systems in Microgrid with Improving Reliability and Energy Efficiency

Author

Listed:
  • R. M. Romero

    (Universidad Brazil)

  • Maria Zelinskaya

    (Kuban State Agrarian University Named After I.T. Trubilin)

  • Samariddin Makhmudov

    (Termez University of Economics and Service
    Alfraganus University
    Tashkent State University of Economics)

  • Sindor Sapaev

    (Urgench State University)

  • Jabbarov Umarbek Rustambekovich

    (Mamun University)

Abstract

A microgrid that utilises renewable energy sources is viewed as the most appropriate and cost-effective method to supply electricity. As technology has progressed, energy storage systems have become a viable alternative for stationary power applications, aiding in alleviating the inconsistent characteristics of renewable energy sources. This study investigates the management of energy within a microgrid by incorporating energy storage systems. The innovative hybrid strategy is used in this research merges the Similarity-Navigated Graph Neural Network with Tasmanian Devil Optimisation. The primary aim of this approach is to enhance energy efficiency and improve reliability in the microgrid system. In this framework, Tasmanian Devil Optimisation is employed to fine-tune the parameters of the system while the Similarity-Navigated Graph Neural Network is tasked with predicting these optimised parameters. To implement this proposed methodology, MATLAB software has been utilised, and the current technique is applied to evaluate its performance. The findings indicate that this approach surpasses all existing methods. Notably, the results demonstrate that the proposed method achieves an outstanding efficiency significantly outperforming other contemporary techniques.

Suggested Citation

  • R. M. Romero & Maria Zelinskaya & Samariddin Makhmudov & Sindor Sapaev & Jabbarov Umarbek Rustambekovich, 2025. "Modelling and Optimal Utilisation of the Renewable Energy Systems in Microgrid with Improving Reliability and Energy Efficiency," SN Operations Research Forum, Springer, vol. 6(3), pages 1-20, September.
  • Handle: RePEc:spr:snopef:v:6:y:2025:i:3:d:10.1007_s43069-025-00494-1
    DOI: 10.1007/s43069-025-00494-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43069-025-00494-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s43069-025-00494-1?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.

    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:spr:snopef:v:6:y:2025:i:3:d:10.1007_s43069-025-00494-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.