ARIMA stochastic models for prediction of energy variables
DOI:
https://doi.org/10.21754/tecnia.v9i1.443Keywords:
Stochastic, models, univariate time series analysis, autoregressive integrated moving average, energy variables, Energy planningAbstract
ARIMA univariate time series analysis were used for modeling and forecasting future energy production and consumption in Asturias-Spain. Initially, each series was recorder monthly from 1980 to 1996. These data include trend and seasonal variations wich allow the use of ARIMA (AutoRegressive Integrated Moving Average) univariate models for predictions of future behavioral patterns. The optimum forecasting models obtained for each energetic series, have a satisfactory degree of statistical validity (Low approximation errors) and are suitable for use as reference inputs in the Regional Energetic Plan of Asturias.
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