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- W4382073734 endingPage "113318" @default.
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- W4382073734 abstract "Weather data is a key input to achieve reliable building energy simulation, and in current studies, EnergyPlus Weather (EPW) data, historically measured by a few suburban weather stations, is the most widely used. However, weather is shaped by urban morphology and other factors, so transforming weather files for the urban context using tools such as Urban Weather Generator becomes necessary. This study investigated the differences between multi-sourced weather datasets after transforming, and, in turn, the subsequent impact on urban building energy simulation. As a case study, one campus block was selected, with 41 urban blocks and their urban morphologies obtained. One microclimate station and 16 sensors were then installed to collect weather data to validate multi-sourced weather files for energy simulation models. The study results showed the root mean square error of temperature differences between suburban weather station, EPW and on-campus microclimate was 2.1 °C and 4.3 °C, respectively, before transforming and 1.2 °C and 4.1 °C, respectively, after transforming. Regarding building energy use, the mean absolute percentage difference (MAPD) of cooling-energy use intensity (EUI) between those calculated using the three datasets was 32.4% and 13.1%, respectively, before transforming and 25.8% and 4.1%, respectively, after transforming. Meanwhile, the MAPD of heating-EUI was 27.2% and 116.3%, respectively, before transforming and 12.7% and 93.6%, respectively, after transforming. This study results provide a reference for selecting weather data for urban building energy modelling to achieve a reliable energy decision-making process." @default.
- W4382073734 created "2023-06-27" @default.
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- W4382073734 date "2023-09-01" @default.
- W4382073734 modified "2023-09-27" @default.
- W4382073734 title "Transforming and validating urban microclimate data with multi-sourced microclimate datasets for building energy modelling at urban scale" @default.
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- W4382073734 doi "https://doi.org/10.1016/j.enbuild.2023.113318" @default.
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