New Method of Modeling Daily Energy Consumption

Krzysztof Karpio (), Piotr Łukasiewicz and Rafik Nafkha
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Krzysztof Karpio: Institute of Information Technology, Warsaw University of Life-SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland
Piotr Łukasiewicz: Institute of Information Technology, Warsaw University of Life-SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland
Rafik Nafkha: Institute of Information Technology, Warsaw University of Life-SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland

Energies, 2023, vol. 16, issue 5, 1-24

Abstract: At present, papers concerning energy consumption and forecasting are predominantly dedicated to various known techniques and their combinations. On the other hand, the research on load modeling and forecasting methodologies is quite limited. This paper presents a new approach concerning hourly energy consumption using a multivariate linear regression model. The proposed technique provides a way to accurately model day-to-day energy consumption using just a few selected variables. The number of data points required to describe a whole day’s consumption depends on the demanded precision, which is up to the user. This model is self-configurable and very fast. The applied model shows that four hours are sufficient to describe energy consumption during the remainder of a given day. We show that for about 84% of the data points, the relative error of the model is below 2.5%, and for all the data points the error does not exceed 7.5%. We obtained a mean relative uncertainty of 1.72% in the learning data set, and 1.69% and 1.82% in the two testing data sets, respectively. In addition, we conclude that the model can also detect days with unusual energy consumption.

Keywords: data mining; machine learning; linear regression; time series; outliners (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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