IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v331y2025ics0360544225025460.html
   My bibliography  Save this article

Analytical-approximation mathematical model of a 500 MW-class CCGT unit for simulation and prediction applications

Author

Listed:
  • Trawiński, Paweł
  • Badyda, Krzysztof

Abstract

The principal objective of this paper was to formulate an original methodology for the development of mathematical models of Combined Cycle Gas Turbine (CCGT) units, using as a case study a 500 MW-class unit operating in cogeneration technology, resulting in the simultaneous production of electricity and district heat, with the additional capability of exporting process steam. The modelling scope addressed key challenges, including: performance maps, expansion lines of exhaust gas and steam, and heat transfer in the heat recovery steam generator and district water heaters. The model was developed using an analytical-approximation approach and included technological limitations imposed by the implemented automatic control systems. A comprehensive validation of the model was conducted, and selected performance characteristics of the cycle were determined. The model demonstrated a highly accurate representation of the CCGT unit's performance, with mean absolute and relative errors for the electrical power output of the gas turbine and steam turbine units equal to 1.18 MW (0.54 %) and 0.63 MW (0.55 %), respectively. The proposed methodology enables off-design simulation of the unit's operation, supports thermal diagnostics of the individual thermal-flow systems, and allows for multi-criteria evaluation of the cycle's performance as a function of varying external conditions.

Suggested Citation

  • Trawiński, Paweł & Badyda, Krzysztof, 2025. "Analytical-approximation mathematical model of a 500 MW-class CCGT unit for simulation and prediction applications," Energy, Elsevier, vol. 331(C).
  • Handle: RePEc:eee:energy:v:331:y:2025:i:c:s0360544225025460
    DOI: 10.1016/j.energy.2025.136904
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225025460
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.136904?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

    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:eee:energy:v:331:y:2025:i:c:s0360544225025460. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.