IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v22y1997i6p579-589.html
   My bibliography  Save this article

EDSSF: A decision support system (DSS) for electricity peak-load forecasting

Author

Listed:
  • Badri, Masood A.
  • Al-Mutawa, Ahmed
  • Davis, Donald
  • Davis, Donna

Abstract

Electricity authorities in the UAE have not been successful in developing reliable and accurate models of system peak load. In this study, we develop a time-series-based decision-support system that integrates data management, model base management, simulation, graphic display, and statistical analysis to provide near-optimal forecasting models. The model base includes a variety of time-series techniques, such as exponential smoothing, Box-Jenkins (BJ), and dynamic regression. The system produces short-term forecasts (one year ahead) by analyzing the behavior of monthly peak loads. The performance of the DSS is validated through a comparison with results suggested by econometricians.

Suggested Citation

  • Badri, Masood A. & Al-Mutawa, Ahmed & Davis, Donald & Davis, Donna, 1997. "EDSSF: A decision support system (DSS) for electricity peak-load forecasting," Energy, Elsevier, vol. 22(6), pages 579-589.
  • Handle: RePEc:eee:energy:v:22:y:1997:i:6:p:579-589
    DOI: 10.1016/S0360-5442(96)00163-6
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544296001636
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/S0360-5442(96)00163-6?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.

    Citations

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


    Cited by:

    1. Marco Barassi & Yuqian Zhao, 2018. "Combination Forecasting of Energy Demand in the UK," The Energy Journal, , vol. 39(1_suppl), pages 209-238, June.
    2. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    3. Mirlatifi, A.M. & Egelioglu, F. & Atikol, U., 2015. "An econometric model for annual peak demand for small utilities," Energy, Elsevier, vol. 89(C), pages 35-44.

    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:eee:energy:v:22:y:1997:i:6:p:579-589. 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.