IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i11p2794-d1410177.html
   My bibliography  Save this article

Maximizing Solar Share in Robust System Spinning Reserve-Constrained Economic Operation of Hybrid Power Systems

Author

Listed:
  • Rana Muhammad Musharraf Saeed

    (Department of Electrical Engineering, The Superior University, Lahore 54000, Pakistan)

  • Naveed Ahmed Khan

    (Independent Researcher, Islamabad 45550, Pakistan)

  • Mustafa Shakir

    (Department of Electrical Engineering, The Superior University, Lahore 54000, Pakistan)

  • Guftaar Ahmad Sardar Sidhu

    (Department of Electrical and Computer Engineering, COMSATS University, Park Road, Chak Shahzad, Islamabad 45550, Pakistan)

  • Ahmed Bilal Awan

    (Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman 346, United Arab Emirates)

  • Mohammad Abdul Baseer

    (People-Centred Artificial Intelligence, Faculty of Engineering and Sciences, University of Surrey, Guildford GU27XH, UK)

Abstract

The integration of renewable energy is rapidly leading the existing grid systems toward modern hybrid power systems. These hybrid power systems are more complex due to the random and intermittent nature of RE and involve numerous operational challenges. This paper presents the operational model for solar integrated power systems to address the issues of economical operation, reliable solar share, energy deficit in case of contingency events, and the allocation of system spinning reserve. A mixed-integer optimization is formulated to minimize the overall cost of the system operation and to maximize the solar share under robust system spinning reserve limits as well as various other practical constraints. A Pareto-optimal solution for the maximization of the number of solar power plants and minimization of the solar cost is also presented for reliable solar share. Further, a decomposition framework is proposed to split the original problem into two sub-problems. The solution of joint optimization is obtained by exploiting a Lagrange relaxation method, a binary search Lambda iteration method, system spinning reserve analysis, and binary integer programming. The proposed model was implemented on an IEEE-RTS 26 units system and 40 solar plants.

Suggested Citation

  • Rana Muhammad Musharraf Saeed & Naveed Ahmed Khan & Mustafa Shakir & Guftaar Ahmad Sardar Sidhu & Ahmed Bilal Awan & Mohammad Abdul Baseer, 2024. "Maximizing Solar Share in Robust System Spinning Reserve-Constrained Economic Operation of Hybrid Power Systems," Energies, MDPI, vol. 17(11), pages 1-22, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2794-:d:1410177
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/11/2794/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/11/2794/
    Download Restriction: no
    ---><---

    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:17:y:2024:i:11:p:2794-:d:1410177. 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: 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.