Forecasting residential electric power consumption for Bogotá Colombia using regression models

This study presents three models of multiple linear regressions for forecasting energy demand. The first is a simple multiple linear regression, the second model has an economic interpretation of coefficients (econometric), while the third model is developed in the form of double logarithm economic...

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Bibliographic Details
Published in:Energy reports 2020-02, Vol.6 (1), p.561-566
Main Authors: Peña-Guzmán, Carlos, Rey, Juliana
Format: Article
Language:English
Subjects:
Energy demand
Forecasting
Multiple linear regressions
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Summary:This study presents three models of multiple linear regressions for forecasting energy demand. The first is a simple multiple linear regression, the second model has an economic interpretation of coefficients (econometric), while the third model is developed in the form of double logarithm economic regression. The article was developed based on the six socio-economic strata in Bogotá City. The second model is shown to be superior to the multiple linear regression model with a climatic approach and the econometric model of double logarithm in terms of precision in the calculation of the electric energy demand, as evidenced in the model evaluation tools used, such as the coefficient of determination, with values higher than 0.9 except in stratum 5.
ISSN:2352-4847
2352-4847
DOI:10.1016/j.egyr.2019.09.026