气候变化领域集成服务门户(CCPortal): Forecasting Chilled Water Consumption under Climate Change: Regression Analysis of University Campus Buildings

CCPortal

	Forecasting Chilled Water Consumption under Climate Change: Regression Analysis of University Campus Buildings
	Im H.; Srinivasan R.; Jia M.
发表日期	2020
起始页码	896
结束页码	904
英文摘要	This paper discusses the development of a forecasting model for university campus energy use under climate change. University campuses are gradually modifying their building energy and environmental policies towards carbon neutrality. Particularly with the changing climate, a dynamic forecasting model is needed that can be used by the university administrators to forecast the demand of energy consumption, e.g., chilled water use. The model development follows a three-step process: (1) data collection and cleaning, (2) descriptive statistics, and (3) statistical modeling. While the dependent variable is chilled water consumption, the independent variables are U-factor of roof, U-factor of walls, U-factor of windows, window wall ratio, lighting power density, equipment power density, building age, building age after latest year of renovation, temperature, humidity, pressure, and wind speed. For training and testing, historical weather data is used. The validated model is used to estimate energy use with future weather data. Prior to modeling, matrix plots and histograms were used to identify correlations between variables, which is followed by data transformation and normalization. Finally, a non-linear regression model was developed to predict the chilled water consumption under climate change. A key finding of the model is that temperature is the most significant variable in chilled water consumption. In addition, building height, building age, and U-factor of walls were found to be important in descending importance. Based on the regression analysis, it was found that chilled water consumption will increase almost three times in the year 2054. © 2020 American Society of Civil Engineers.
scopus关键词	Climate models; Cooling water; Energy utilization; Environmental protection; Forecasting; Linear transformations; Metadata; Regression analysis; Walls (structural partitions); Water supply; Wind; Descriptive statistics; Environmental policy; Historical weather datum; Independent variables; Lighting power density; Non-linear regression; Significant variables; Statistical modeling; Climate change
来源期刊	Construction Research Congress 2020: Computer Applications - Selected Papers from the Construction Research Congress 2020
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/176713
作者单位	Univ. of Florida, Rinker School of Construction Management, Gainesville, FL, United States
推荐引用方式 GB/T 7714	Im H.,Srinivasan R.,Jia M.. Forecasting Chilled Water Consumption under Climate Change: Regression Analysis of University Campus Buildings[J],2020.
APA	Im H.,Srinivasan R.,&Jia M..(2020).Forecasting Chilled Water Consumption under Climate Change: Regression Analysis of University Campus Buildings.Construction Research Congress 2020: Computer Applications - Selected Papers from the Construction Research Congress 2020.
MLA	Im H.,et al."Forecasting Chilled Water Consumption under Climate Change: Regression Analysis of University Campus Buildings".Construction Research Congress 2020: Computer Applications - Selected Papers from the Construction Research Congress 2020 (2020).