Energy consumption estimate of a house

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Published: Nov 6, 2020
Keywords:
regression, sizing, energy, comparison, forecast

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Diego Andrés Bautista López
Maria Paula Mantilla Arias

Abstract

This paper presents the results of the comparison between three different numeric regression techniques used to forecast typical home electric power consumption values. The data used was real life hourly consumption data gathered from homes in the “Cooservicios” community of the city of Tunja (Colombia). The results of the study suggest that a regression technique based on the comparison between the average and daily values yields the lowest Mean Square Error (MSE). Once the MSE is deemed acceptable, it is possible to utilize the model to forecast power consumption with a relative degree of confidence. This comparison is made with the purpose of improving the dimensioning of renewable energy systems, based on the electricity consumption determined according to the predictions, achieving efficient systems that meet the needs of each one of the homes.

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How to Cite
Bautista López, D. A., & Mantilla Arias, M. P. (2020). Energy consumption estimate of a house. Ingenio Magno, 11(1), 88-97. Retrieved from http://revistas.ustatunja.edu.co/index.php/ingeniomagno/article/view/2051
Issue
Vol. 11 No. 1 (2020): Ingenio Magno vol. 11-1
Section
Artículos Vol. 11-1

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Author Biographies

Diego Andrés Bautista López

Facultad de Ingeniería, Escuela de Ingeniería Electrónica, Semillero de Investigación S-PERD, Grupo de Investigación I2E, Universidad Pedagógica y Tecnológica de Colombia.

Maria Paula Mantilla Arias

Facultad de Ingeniería, Escuela de Ingeniería Electrónica, Semillero de Investigación S-PERD, Grupo de Investigación I2E, Universidad Pedagógica y Tecnológica de Colombia.

References

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