Issue |
E3S Web Conf.
Volume 111, 2019
CLIMA 2019 Congress
|
|
---|---|---|
Article Number | 06009 | |
Number of page(s) | 8 | |
Section | Sustainable Urbanization and Energy System Integration | |
DOI | https://doi.org/10.1051/e3sconf/201911106009 | |
Published online | 13 August 2019 |
Analysis of energy signatures and planning of heating and domestic hot water energy use in buildings in Norway
1 Department of Energy and Process Technology, Norwegian University of Science and Technology (NTNU), Kolbjørn Hejes vei 1 B, Trondheim 7491, Norway
2 SINTEF, Department of Building and Infrastructure, P.O. Box 124 Blindern, 0314 Oslo, Norway
* Corresponding author: tymofii.tereshchenko@ntnu.no
Widespread introduction of low energy buildings (LEBs), passive houses, and zero emission buildings (ZEBs) are national target in Norway. In order to achieve better energy performance in these types of buildings and successfully integrate them in energy system, reliable planning and prediction techniques for heat energy use are required. However, the issue of energy planning in LEBs currently remains challenging for district heating companies. This article proposed an improved methodology for planning and analysis of domestic hot water and heating energy use in LEBs based on energy signature method. The methodology was tested on a passive school in Oslo, Norway. In order to divide energy signature curve on temperature dependent and independent parts, it was proposed to use piecewise regression. Each of these parts were analyzed separately. The problem of dealing with outliers and selection of the factors that had impact of energy was considered. For temperature dependent part, the different methods of modelling were compared by statistical criteria. The investigation showed that linear multiple regression model resulted in better accuracy in the prediction than SVM, PLS, and LASSO models. In order to explain temperature independent part of energy signature the hourly profiles of energy use were developed.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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