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The summertime overheating signature of homes
conference contributionposted on 11.01.2022, 09:54 authored by Paul DruryPaul Drury, Arash BeizaeeArash Beizaee, Kevin LomasKevin Lomas
Summertime overheating of homes has been demonstrated in many countries. Raised internal temperatures have a detrimental impact on health, comfort, and well-being. Climate change is predicted to cause hotter summers in many countries with more frequent and intense heatwaves. There is, therefore, a need to understand the likely overheating risk of homes in these future summers. Simple physics-based models are very limited in their ability to produce valid assessments of overheating. More complex modelling using Dynamic Thermal Simulation (DTS) software can simulate internal temperatures when the modelled building is subject to future weather files. There are, however, acknowledged uncertainties attached to the overheating determined from these simulations. Data-driven models can use temperature monitored in existing buildings to predict future overheating risk. This paper presents the idea of ‘overheating signatures’, simple mathematical models which relate the internal temperature in spaces to the external conditions and occupant behaviour. Synthetic data from a single-zone building was used to derive such models and evaluate their ability to ‘predict’ overheating for different UK weather conditions. Analysis of the data revealed that there was a strong correlation between number of hours overheated and the warm period average outdoor air temperature (R2 above 0.94). Applying the regression model to two different UK locations showed high correlation between overheating results predicted by the mathematical model and those from dynamic thermal simulation (R2, 0.94 to 0.98). Based on these findings we conclude that data-driven models have an important role to play in evaluating overheating risk. Future work is, however, needed to refine the mathematical models with data on a daily timescale and to test them on real-world buildings. Although this research has a focus on UK dwellings, it is likely of interest to other countries with a temperate climate.
This work was conducted as part of a research project pursued within the London-Loughborough (LoLo) Centre for Doctoral Training in Energy Demand. The EPSRC funding for the centre is gratefully acknowledged (grant number EPL01517X1).
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