Forecasting Electric Load Demand through Advanced Statistical Techniques
- Bayesian networks
- Decision making
- Bayesian methods
- Colombia
- Electric load demands
- Forecasting models
- Statistical techniques
- Electric load forecasting
Publication date
January 2020
DOIAbstract
Traditional forecasting models have been widely used for decision-making in production, finance and energy. Such is the case of the ARIMA models, developed in the 1970s by George Box and Gwilym Jenkins [1], which incorporate characteristics of the past models of the same series, according to their autocorrelation. This work compares advanced statistical methods for determining the demand for electricity in Colombia, including the SARIMA, econometric and Bayesian methods
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