2022
DOI: 10.1016/j.scs.2021.103634
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High-resolution impact assessment of climate change on building energy performance considering extreme weather events and microclimate – Investigating variations in indoor thermal comfort and degree-days

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Cited by 61 publications
(16 citation statements)
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“…By identifying residential clusters with the percentage of each building archetype in Greater London, the present study can be expanded from the building level to the city level, with a focus on low-income households. This is crucial for future energy planning and policymaking, considering the complexities and interconnections of extreme events [15], including wars (such as in Ukraine), particularly for low-income households, in achieving the energy and climate targets set for 2050.…”
Section: Discussionmentioning
confidence: 99%
“…By identifying residential clusters with the percentage of each building archetype in Greater London, the present study can be expanded from the building level to the city level, with a focus on low-income households. This is crucial for future energy planning and policymaking, considering the complexities and interconnections of extreme events [15], including wars (such as in Ukraine), particularly for low-income households, in achieving the energy and climate targets set for 2050.…”
Section: Discussionmentioning
confidence: 99%
“…These phenomena play a decisive role not only in the formation of natural and climatic factors of the area, but also in changing the environment of the areas of human activity [2,3,4].…”
Section: Methodsmentioning
confidence: 99%
“…Moreover, accurately forecasting buildings electricity load is challenging due to the dynamic and diverse nature of occupant behaviors, which are often not directly observable. Occupancy data is crucial [4,21] but difficult to obtain due to privacy concerns, the absence of occupancy sensors in legacy buildings, high sensor installation costs, and issues related to sensor accuracy. Researchers have explored various proxy information sources for occupancy sensing, such as Google search trends [15], positional records from Twitter [28], Call Details Recore [8], Wi-Fi-derived occupancy [29], Bluetooth low energy on mobile devices [43], domestic water consumption [16], and indoor carbon dioxide measurements [46].…”
Section: Human Mobility As a Proxy To Occupancy Behaviourmentioning
confidence: 99%