Short-term forecasting of industrial electricity consumption in Brazil
Article Abstract:
A short-term forecasting of industrial electricity consumption in Brazil utilized two unique approaches: dynamic non-linear modelling and econometric or regression modelling. The former approach was based on structural dynamic models for multiple time series analysis and forecasting while the latter method was based on popular econometric models and adopted by electricity power utilities. The comparison of these results introduced a non-linear method of analysis and forecasting for a vector time series with a multiplicative seasonal component shared by the marginal series.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1999
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One-day prediction of electricity load reflecting future RCS schedule
Article Abstract:
A one-day electricity load forecasting model is presented. The linear model is influenced by a West Bohemian power company's ripple control system (RCS), which specifically incorporates the separation of the total load into the RCS and the baseload. Manipulation is thus allowed by rescheduling the RCS and its corresponding regressors. The model is designed for the daily planning and activities of a dispatcher.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1996
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Modelling the impact of temperature on electricity consumption in the Eastern Province of Saudi Arabia
Article Abstract:
A forecasting model for the assessment of the impact of ambient temperature on electricity consumption was developed using monthly electricity consumption data for the Eastern Province of Saudi Arabia. Results indicated that yearly regression models provide better results than models covering longer periods. Furthermore, electricity demand and consumption are shown to be affected by changes in temperature.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1996
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