IDEAS home Printed from https://ideas.repec.org/a/hin/jijmms/9308174.html
   My bibliography  Save this article

The Measures of Efficiency of Power Generation Plants in Sylhet of Bangladesh

Author

Listed:
  • Kanis Fatama Ferdushi
  • Anton Abdulbasah Kamil
  • Saleh Ahmed
  • Luthful Alahi Kawsar

Abstract

This study measures the performance of power generation plants in Sylhet region of Bangladesh considering twenty-four-month monthly dataset during 2013-14. To measure the performance of those plants, gross electricity generation was considered as output for the stochastic frontier model, whereas fuel consumption, lube oil consumption, auxiliary consumption, cost, heat rate, and hours of run were considered as input variables. Based on the log-likelihood hypothesis test, trans-log production model is preferred over Cobb–Douglas (C-D) production model for this study. The average efficiency of the selected plants is above 90 percent, and there is Sylhet Combined Cycle Power Plant (CCPP) which has an efficiency of about 78.6 percent for truncated normal distribution. In the time-variant inefficiency effects model, fuel consumption, cost, square product of lube oil consumption, interaction between fuel consumption and lube oil consumption as well as auxiliary consumption, and hours of run have a significant positive influence on power generation. On the other hand, some input variables such as hours of run and interaction between cost and heat rate have a significant negative influence on power generation. The estimated values of the time-varying inefficiency parameter are positive for both the truncated and the half-normal distribution. This result indicates that technical efficiency has declined over the reference period of the study.

Suggested Citation

  • Kanis Fatama Ferdushi & Anton Abdulbasah Kamil & Saleh Ahmed & Luthful Alahi Kawsar, 2020. "The Measures of Efficiency of Power Generation Plants in Sylhet of Bangladesh," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2020, pages 1-9, May.
  • Handle: RePEc:hin:jijmms:9308174
    DOI: 10.1155/2020/9308174
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/IJMMS/2020/9308174.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/IJMMS/2020/9308174.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2020/9308174?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
    ---><---

    More about this item

    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:hin:jijmms:9308174. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.