IDEAS home Printed from https://ideas.repec.org/a/apa/ijtess/2017p147-158.html
   My bibliography  Save this article

Forecast Rainfall for Power Production Management of Namkhan 2 and 3 Hydropower Plants

Author

Listed:
  • N. BANGSULIN

    (Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand)

  • A. PROMWUNGKWA

    (Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand)

  • K. NGAMSANROAJ

    (Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand)

Abstract

The objective of this research is to study rainfall and to forecast reservoir management for optimal electricity production for Namkhan 2 and 3 hydropower plants. The statistical data used is 50 years’ data from the years 1960 to 2009, which is used to predict the rainfall in the future year of 2016. Forecasting algorithms are (1) Forecasts Function in Microsoft Excel (FFME), (2) Minitab software (MNT), (3) Statistical Package for Social Sciences (SPSS), and (4) Fast Fourier Transform (FFT). The SPSS method provides most accurate results as compared to the others, which is 2.9% different from the actual data. The forecast results are next used as input data for a simulation model for optimizing reservoir management of both hydropower plants. Simulation software is HEC-ResSim3.1, which is used for operations testing for electricity production and water regulation. The input data are the technical data of both HPP and the monthly forecasted rainfall. This study shows that possibility to use the recorded data to predict near future data, which is used as input in the optimization software. The simulation benefits a hydropower plant operator to plan the optimal electricity production.

Suggested Citation

  • N. Bangsulin & A. Promwungkwa & K. Ngamsanroaj, 2017. "Forecast Rainfall for Power Production Management of Namkhan 2 and 3 Hydropower Plants," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 3(4), pages 147-158.
    • Handle: RePEc:apa:ijtess:2017:p:147-158
    DOI: 10.20469/ijtes.3.40003-4
    as

    Download full text from publisher

    File URL: https://kkgpublications.com/technology-engineering-studies-volume-3-issue-4/
    Download Restriction: no
    File URL: https://kkgpublications.com/wp-content/uploads/2018/09/ijtes.3.40003.4.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.20469/ijtes.3.40003-4?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Walaiporn Singkhamfu & Kanokwan Chaiyaso & Narisra Laohapatanalert & Nikom Thipnate & Phudinan Singkhamfu, 2018. "The Real-Time Power Monitoring in Building Using IoT Sensing Method and Knowledge Management Approach," Journal of ICT, Design, Engineering and Technological Science, Juhriyansyah Dalle, vol. 2(2), pages 36-39.

    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:apa:ijtess:2017:p:147-158. 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: PROF.IR.DR.Mohid Jailani Mohd Nor (email available below). General contact details of provider: https://kkgpublications.com/technology/ .

    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.