Abstract
The study considered providing the best model among competing models for forecasting electricity load demand. Data from Helios Towers was used for this purpose. The study applied the Autoregressive Integrated Moving Average (ARIMA) model and residuals from the model tested for heteroscedasticity. The residuals were found to be heteroscedastic, thus, the Autoregressive Conditional Heteroscedastic (ARCH) and the Generalized Autoregressive Conditional Heteroscedastic (GARCH) models were applied to the data set. Competing models namely, ARCH (1), ARCH (2), ARCH (3) and GARCH (1, 1) models were fitted to the demand data under study. Based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) approach, the best heteroscedastic model was the ARCH (2). The study thus used the ARIMA (3, 0, 4)-ARCH (2) model for a two-point forecast of electricity load demand.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
