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As summer heat events cause a further increase of heat load in buildings, the need for indoor overheating assessment by building performance simulations (BPS) for planning is rising. Besides other boundary conditions, the selection of proper weather data is known to significantly influence the outcome of overheating evaluation. Our research pointed out that current standards do not consider weather data including regional differences, urban climate effects or future climate in a sufficient way. We suggest a new approach to create weather data sets for an average present and an average future summer based on meteorological data from weather stations. Therefore, we define characteristic summer values as indicators. In addition, urban climate is taken into account by mapping the outdoor temperature differences between urban areas and surrounding countryside using Local Climate Zones. We analyse the developed weather data sets for four regions in Germany by comparing the indoor overheating risk by BPS for an exemplary building. The results show that the overheating risk differs significantly between the regions. It is very low for the region of Hamburg, moderate for Dresden and Potsdam and highly critical for Stuttgart. The indoor heat load is at least more than doubled if the building is located in the city centre instead of its surroundings or if future climate conditions are applied. Furthermore, high night-time outdoor temperatures appear to significantly increase indoor overheating. Our approaches are first suggestions and show the relevance of regional and urban climate for indoor overheating assessment by BPS.
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Tim Felix Kriesten
Leibniz Institute of Ecological Urban and Regional Development
Astrid Ziemann
Technische Universität Dresden
Valeri Goldberg
Hochschule für Technik und Wirtschaft Dresden – University of Applied Sciences
City and Environment Interactions
Technische Universität Dresden
Leibniz Institute of Ecological Urban and Regional Development
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Kriesten et al. (Thu,) studied this question.
synapsesocial.com/papers/68e5cff5b6db643587566481 — DOI: https://doi.org/10.1016/j.cacint.2024.100163
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