SciELO - Scientific Electronic Library Online

 
vol.23 issue3Evaluation of a second order simulation for Sterling engine design and optimisation author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

    Related links

    • On index processCited by Google
    • On index processSimilars in Google

    Share


    Journal of Energy in Southern Africa

    On-line version ISSN 2413-3051Print version ISSN 1021-447X

    Abstract

    CHIKOBVU, Delson  and  SIGAUKE, Caston. Regression-SARIMA modelling of daily peak electricity demand in South Africa. J. energy South. Afr. [online]. 2012, vol.23, n.3, pp.23-30. ISSN 2413-3051.

    In this paper, seasonal autoregressive integrated moving average (SARIMA) and regression with SARIMA errors (regression-SARIMA) models are developed to predict daily peak electricity demand in South Africa using data for the period 1996 to 2009. The performance of the developed models is evaluated by comparing them with Winter's triple exponential smoothing model. Empirical results from the study show that the SARIMA model produces more accurate short-term forecasts. The regression-SARIMA modelling framework captures important drivers of electricity demand. These results are important to decision makers, load forecasters and systems operators in load flow analysis and scheduling of electricity.

    Keywords : daily peak demand; SARIMA; regression-SARIMA; short term load forecasting.

            · text in English     · English ( pdf )