Overheating exposure over time can lead to discomfort, productivity reduction, and health issues for the occupants in buildings. The time-integrated overheating evaluation methods are introduced to describe, in a synthetic way, the extent of overheating over a span of time and predict the uncomfortable phenomena. This paper reviews the time-integrated overheating evaluation methods that are applicable to residential buildings in temperate climates of Europe. We critically analyze the methods found in (i) 11 international standards, namely,
Over the last decades overheating in buildings has become a major concern. The situation is expected to worsen due to the current rate of climate change. Many efforts have been made to evaluate the future thermal performance of buildings and cooling technologies. In this paper, the term "climate change overheating resistivity" of cooling strategies is defined, and the calculation method is provided. A comprehensive simulation-based framework is then introduced, enabling the evaluation of a wide range of active and passive cooling strategies. The framework is based on the Indoor Overheating Degree (IOD), Ambient Warmness Degree (AWD), and Climate Change Overheating Resistivity (CCOR) as principal indicators allowing a multi-zonal approach in the quantification of indoor overheating risk and resistivity to climate change.To test the proposed framework, two air-based cooling strategies including a Variable Refrigerant Flow (VRF) unit coupled with a Dedicated Outdoor Air System (DOAS) (C01) and a Variable Air Volume (VAV) system (C02) are compared in six different locations/climates. The case study is a shoe box model representing a double-zone office building. In general, the C01 shows higher CCOR values between 2.04 and 19.16 than the C02 in different locations. Therefore, the C01 shows superior resistivity to the overheating impact of climate change compared to C02. The maximum CCOR value of 37.46 is resulted for the C01 in Brussels, representing the most resistant case, whereas the minimum CCOR value of 9.24 is achieved for the C02 in Toronto, representing the least resistant case.
Abstract. Increasing temperatures due to global warming will influence
building, heating, and cooling practices. Therefore, this data set aims to
provide formatted and adapted meteorological data for specific users who
work in building design, architecture, building energy management
systems, modelling renewable energy conversion systems, or others
interested in this kind of projected weather data. These meteorological data
are produced from the regional climate model MAR (Modèle
Atmosphérique Régional in French) simulations. This regional model,
adapted and validated over Belgium, is forced firstly, by the ERA5 reanalysis,
which represents the closest climate to reality and secondly, by three Earth system models (ESMs) from
the Sixth Coupled Model Intercomparison Project database, namely,
BCC-CSM2-MR, MPI-ESM.1.2, and MIROC6. The main advantage of using the MAR
model is that the generated weather data have a high resolution (hourly data
and 5 km) and are spatially and temporally homogeneous. The generated weather
data follow two protocols. On the one hand, the Typical Meteorological Year
(TMY) and eXtreme Meteorological Year (XMY) files are generated largely
inspired by the method proposed by the standard ISO15927-4, allowing the
reconstruction of typical and extreme years, while keeping a plausible
variability of the meteorological data. On the other hand, the heatwave
event (HWE) meteorological data are generated according to a method used to
detect the heatwave events and to classify them according to three criteria
of the heatwave (the most intense, the longest duration, and the highest
temperature). All generated weather data are freely available on the open
online repository Zenodo (https://doi.org/10.5281/zenodo.5606983,
Doutreloup and Fettweis, 2021) and these data are produced within
the framework of the research project OCCuPANt
(https://www.occupant.uliege.be/ (last access: 24 June 2022) – ULiège).
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