Urban residential energy consumption modeling in the Integrated Urban Metabolism Analysis Tool (IUMAT)

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• 作者：Nariman Mostafavi^a ; ^{sm3892@drexel.edu} ; Mohamad Farzinmoghadam^b ; ^{mfarzinmoghadam@wpi.edu} ; Simi Hoque^a ; ^{simi@coe.drexel.edu}
• 关键词：Urban metabolism ; Urban energy modeling ; Energy consumption ; Residential energy use ; IUMAT ; Quantile regression
• 刊名：Building and Environment
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：114
• 期：Complete
• 页码：429-444
• 全文大小：4112 K
• 卷排序：114

文摘

Quantile regression is used to predict residential energy use categories. A method for calculating GHG emissions for residential energy use is introduced. The use of actual datasets for energy modeling and policy making is evaluated. Prediction power for HVAC energy use is scale-dependent, unlike other categories. Pricing and retrofit strategies do not impact energy savings in some categories.