•A low-cost fisheye lens and a smartphone quantify the shading correction factor.•The method does not require 3D building design or angle measurements.•The model correctly predicts the real Sun’s ...position in the photos.•The model correctly predicts the expected window shading.•Standard tabulated values do not take into account overlapping shading.
Quasi-steady-state methods to calculate monthly heating and cooling energy needs require the quantification of solar heat gains through windows. The presence of external obstacles, such as natural topography, other buildings, overhangs, or side fins, may significantly decrease solar gains. Simplified methods to evaluate shading on windows throughout the year use the shading correction factor concept, i.e., the ratio between the surface solar irradiation in the presence of external obstacles and in their absence. This paper presents a photographic method using a low-cost fisheye lens attached to a smartphone to quantify the shading correction factor. It is based on image processing, solar geometry, and climate databases and does not require 3D building design or angle measurement of external obstacles. Both beam and diffuse correction factors are calculated monthly. The model correctly predicts the real Sun’s position in the photos and the expected monthly shading of a South window with an overhang. For the diffuse correction factor, errors up to 11% are obtained when compared to the analytical solution of a window with a large overhang. Standard tabulated values for windows with multiple obstructions are conservative when compared to those of the photographic method. The tabulated approach considers the effect of various obstacles shading even when overlapping occurs, which possibly explains the difference between methods.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Many studies have investigated the accuracy of the numerical parameters in the application of the quasi steady-state calculation method. The aim of this study is to derive the reference numerical ...parameters of the ISO 13790 monthly method by reflecting the surface-to-volume (S/V) ratio and the characteristics of the structures. The calculation process was established, and the parameters necessary to derive the reference numerical parameters were calculated based on the input data prepared for the established calculation processes. The reference numerical parameters were then derived through regression analyses of the calculated parameters and the time constant. The parameters obtained from an apartment building and the parameters of the international standard were both applied to the Passive House Planning Package (PHPP) and EnergyPlus programs, and the results were analyzed in order to evaluate the validity of the results. The analysis revealed that the calculation results based on the parameters derived from this study yielded lower error rates than those based on the default parameters in ISO 13790. However, the differences were shown to be negligible in the case of high heat capacity.
Für die Berechnung des Energiebedarfs für Heizung und Kühlung können drei Verfahren gleichberechtigt eingesetzt werden: das ausführliche dynamische Simulationsverfahren, das vereinfachte dynamische ...Stundenverfahren und das quasi‐stationäre Monatsverfahren. Diese verschiedenen Verfahren unterscheiden sich maßgeblich in ihrem Detaillierungsgrad und liefern daher Ergebnisse unterschiedlicher Qualität. Zum Vergleich dieser Ergebnisse werden in der Validierungsnorm EN 15265 die Differenzen der Jahreswerte für die Beurteilung verwendet, die Abweichungen der einzelnen Stunden‐ und Monatswerte bleiben jedoch unberücksichtigt. In diesem Artikel wird daher einerseits dargestellt, wie die Standardabweichung der Einzeldifferenzen in die Qualitätsbewertung der Verfahren aufgenommen werden könnte. Andererseits wird aufgezeigt, welche Auswirkungen die einzelnen Posten der Wärmebilanz auf die Qualität der Ergebnisse haben.
Influencing parameters on calculated heating and cooling energy demand in buildings in accordance to various methods of EN ISO 13790. For calculation of energy use for space heating and cooling three methods can be deployed: detailed simulation method, simplified hourly method and simplified monthly method. The different methods differ significantly in terms of level of detail and therefore also in the quality of their results. For the comparison of the results of different models a standard for validation was established, which evaluates the quality of the models based on differences of the annual sums of energy use for heating and cooling. Differences of hourly or monthly values do not influence the validation. This article shows, how mean value and standard deviation can be integrated into the validation method. Furthermore it describes the influence of the elements of the heat balance on the quality of the results.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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