Stochastic time-series modelling for long-term load forecasting

E. F. El-Saadany, M. M.A. Salama, A. Y. Chikhani, K. W. Hipel

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Sometime series models suitable for forecasting are reviewed. Autoregreasive moving average-type (ARMA) time series models, in particular, are well suited for forecasting applications. The procedure of model development, consisting of the identification, estimation, and diagnostic checking stages, make these models convenient to apply to practice. The accuracy of load forecasting can-be improved by increasing the number of observations. Application of these models to Egyptian electricity consumption is presented, and different model forecasts are compared.

Original languageBritish English
Pages (from-to)199-205
Number of pages7
JournalInternational Journal of Power and Energy Systems
Issue number3
StatePublished - 1998


  • Stochastic time-series long-term load modelling


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