Despite known effects of urban heat island(UHI)on building energy consumption such as increased cooling energy demand,typical building energy simulation(BES)practices lack a standardized approach to incorporate UHI in...Despite known effects of urban heat island(UHI)on building energy consumption such as increased cooling energy demand,typical building energy simulation(BES)practices lack a standardized approach to incorporate UHI into building energy predictions.The seasonal and diurnal variation of UHI makes the task of incorporating UHI into BES an especially challenging task,often limited by the availability of detailed hourly temperature data at building location.This paper addresses the temporal variation of UHI by deriving four normalized UHI indicators that can successfully capture the seasonal and diurnal variation of UHI.The accuracy of these indicators was established across four climate types including hot and humid(Miami,FL),hot and dry(Los Angeles,CA),cold and dry(Denver,CO),and cold and humid(Chicago,IL),and three building types including office,hospital,and apartments.These four indicators are mean summer daytime UHI,mean summer nighttime UHI,mean winter daytime UHI,and mean winter nighttime UHI,which can accurately predict cooling,heating,and annual energy consumption with mean relative error of less than 1%.Not only do these indicators simplify the application of UHI to BES but also,they provide a new paradigm for UHI data collection,storage,and usage,specifically for the purpose of BES.展开更多
文摘Despite known effects of urban heat island(UHI)on building energy consumption such as increased cooling energy demand,typical building energy simulation(BES)practices lack a standardized approach to incorporate UHI into building energy predictions.The seasonal and diurnal variation of UHI makes the task of incorporating UHI into BES an especially challenging task,often limited by the availability of detailed hourly temperature data at building location.This paper addresses the temporal variation of UHI by deriving four normalized UHI indicators that can successfully capture the seasonal and diurnal variation of UHI.The accuracy of these indicators was established across four climate types including hot and humid(Miami,FL),hot and dry(Los Angeles,CA),cold and dry(Denver,CO),and cold and humid(Chicago,IL),and three building types including office,hospital,and apartments.These four indicators are mean summer daytime UHI,mean summer nighttime UHI,mean winter daytime UHI,and mean winter nighttime UHI,which can accurately predict cooling,heating,and annual energy consumption with mean relative error of less than 1%.Not only do these indicators simplify the application of UHI to BES but also,they provide a new paradigm for UHI data collection,storage,and usage,specifically for the purpose of BES.
