Abstract

Knowledge of the influence of factors determining energy consumption in buildings is very important for the possibility of effective energy saving. This article describes the results of an original study on the analysis of the annual energy demand for heating (QH;nd), cooling (QC;nd), and annual usable energy demand (QH/C;nd = QH;nd + QC;nd) assumed as objective functions of a designed single-family building, which can be classified as a typical representative of currently built houses in Poland. It was assumed that the object of study was located in the climatic conditions of north-eastern Poland. The study takes into consideration three groups of selected parameters: architectural/spatial, structural, and physical properties of windows. The research was carried out in a single-family building, as energy consumption in residential buildings accounts for a significant part of the total energy consumption in buildings. In the group of architectural/spatial parameters, the height of rooms in the building (h) and the window area change coefficient (k) were taken into consideration. The design parameters pertained to the solutions of building components: the density of the material of the inner layer of the external walls (ρ1), the density of the material of internal walls (ρ2), and the thickness of internal walls (d). In the third group of parameters, the heat transfer coefficient of the glazing (Ug) and the total solar transmittance of the glazing (g) were considered. Deterministic mathematical models of these dependencies were developed on the basis of the results of a computational experiment, obtained by performing a simulation with the use of the DesignBuilder software, based on the EnergyPlus computational engine. The models allowed the authors to estimate the degree and nature of the influence of the examined factors on the building’s energy demand. As a result of the optimization of parameters according to the energy criterion, the contribution of each of the three groups of parameters to energy saving was determined. Deterministic numerical optimization using MATLAB was applied. It turned out that the factors from the first group played the most important role in energy savings (40.0%), and the factors from the third group contributed slightly less (25.7%). The contribution of the characteristics from the second group was 4.2% of the total value of energy saving. This information can be useful to scientists, as well as engineers and policymakers, in making correct decisions when designing new residential buildings.

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