IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v283y2023ics0360544223017619.html
   My bibliography  Save this article

Exergoeconomic and exergoenvironmental analysis and optimization of an integrated double-flash-binary geothermal system and dual-pressure ORC using zeotropic mixtures; multi-objective optimization

Author

Listed:
  • Chen, Ying
  • Liu, Yuxuan
  • Nam, Eun-Young
  • Zhang, Yang
  • Dahlak, Aida

Abstract

The current study focuses on proposing a double-flash geothermal system with a dual-pressure organic Rankine cycle that utilizes zeotropic mixtures. This system aims to harness the geothermal energy efficiently and sustainably. The performance of the system is evaluated using the exergy, exergoeconomic, and exergoenvironmental approaches, taking into account the utilization of different mass fractions of the R123/R142b mixture. The results of the analysis indicate that the designed system is capable of producing a net power output of 6336.04 kW with an exergetic efficiency of 66.70%. The payback period of the system is estimated to be 3.48 years, indicating its economic viability. Moreover, the electricity sale price has a substantial impact on the system's payback period and revenue, surpassing the influence of the geofluid purchase cost. Through the application of triple-objective optimization scenarios, the best optimum state of the system is determined to achieve a 66.96% exergetic efficiency, 3017.82 mPts/h exergoenvironmental impacts, and a payback period of 3.38 years. Furthermore, this state yields a revenue of 11.1 M$. Overall, the study highlights the potential of the proposed double-flash geothermal system with a dual-pressure organic Rankine cycle utilizing zeotropic mixtures for sustainable power generation.

Suggested Citation

  • Chen, Ying & Liu, Yuxuan & Nam, Eun-Young & Zhang, Yang & Dahlak, Aida, 2023. "Exergoeconomic and exergoenvironmental analysis and optimization of an integrated double-flash-binary geothermal system and dual-pressure ORC using zeotropic mixtures; multi-objective optimization," Energy, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223017619
    DOI: 10.1016/j.energy.2023.128367
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223017619
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.128367?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:eee:energy:v:283:y:2023:i:c:s0360544223017619. 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.