Possibilities of predicting heat consumption in a dwelling by autoregression models
author:
GRZEGORZ BARTNICKI, BOGDAN NOWAK
ORCID ID:
0000-0002-4482-6950, 0000-0002-9764-5555
No:
5/2021 Instal p. 08-14
DOI:
10.36119/15.2021.5.1
The article describes the possibilities of using the ARIMA and XGBoost models to predict heat consumption in
dwellings in a multi-family building. Based on the measurement data from the period 2016-2020 of heat
consumption in dwellings in two building complexes, ARIMA and XGBoost models were developed to predict heat
consumption in monthly periods, and the R environment was used for the calculations. The results are presented in
the article for selected apartments in the form of tables and figures. ARIMA models were found to be good, but not
effective for rapid changes in single observations. The applications described in the article also require further
research. XGBoost is a much more advanced algorithm, and consequently there are many more model parameters
that need to be set and optimized later. Therefore, this aspect will be the subject of further research, because despite
the expectation of good results, the use of this algorithm did not give much better prediction for rapid changes than
the ARIMA models.
Keywords:
About Authors:
dr inż. Grzegorz Bartnicki – Katedra Klimatyzacji, Ogrzewnictwa, Gazownictwa i Ochrony Powietrza, Politechnika Wrocławska, https://orcid.org/0000-0002-4482-6950; e-mail: grzegorz.bartnicki@pwr.edu.pl
dr inż. Bogdan Nowak – Katedra Klimatyzacji, Ogrzewnictwa, Gazownictwa i Ochrony Powietrza, Politechnika Wrocławska, https://orcid.org/0000-0002-9764-5555; Correspondence address e-mail: bogdan.nowak@pwr.edu.pl