Energy consumption estimate of a house
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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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With this document, I/We certify that the article submitted for possible publication in the institutional journal INGENIO MAGNO of the Research Center Alberto Magno CIIAM of the University Santo Tomás, Tunja campus, is entirely of my(our) own writing, and is a product of my(our) direct intellectual contribution to knowledge.
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References
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