Modelling of heating energy demand in multi-family buildings depending on meteorological conditions in Wrocław
DOI:
https://doi.org/10.36119/15.2024.5.2Keywords:
regressive decision trees, model of consumption, input variable selection, domestic hot water, heating, meteorological parametersAbstract
Rising energy prices, as well as regulations related to the energy efficiency of buildings, make the issue of energy consumption for heating and hot water preparation analysis a subject of interest for building managers and the scientific community. Furthermore, progressive climate change, with increasingly warmer winters and hotter summers, requires the implementation of deeper analyses of energy intake in relation to the changing meteorological situation. This article presents the modelling results of the energy consumption for heating and hot water preparation, conducted in cooperation with one of Wroclaw’s housing cooperatives. It was shown that with the use of a simple structure of regression decision trees, it is possible to create a model of the heat consumption for multifamily housing, while learning the rules of the impact of weather conditions on this aspect. The determination coefficients R2 of the models oscillated, depending on the building, in the range of 0.93 to 0.96.
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References
Ling J., Dai N., Xing J., Tong H. An Improved Input Variable Selection Method of the Data Driven Model for Building Heating Load Prediction. Journal of Building Engineering 44 (2021), 103255; doi: 10.1016/j.jobe.2021.103255
Salata F., Falasca S., Ciancio V., Curci G., Grignaffini S., de Wilde P. Estimating Building Cooling Energy Demand through the Cooling Degree Hours in a Changing Climate: A Modeling Study. Sustainable Cities and Society 76 (2022), 103518; doi: 10.1016/j.scs.2021.103518
Imhoff M. L., Bounoua L., Ricketts T., Loucks C., Harriss R., Lawrence W. T. Global Patterns in Human Consumption of Net Primary Production. Nature 429(6994) (2004), 870–73; doi: 10.1038/nature02619
