Energy and carbon performance of urban buildings using metamodeling variable importance techniques  

作　　者：Yunliang Liu Wei Tian Xiang Zhou 

机构地区：[1]School of Mechanical Engineering,Tongji University,Shanghai 200092,China [2]Tianjin Key Laboratory of Integrated Design and On-line Monitoring for Light Industry&Food Machinery and Equipment,College of Mechanical Engineering,Tianjin University of Science and Technology,Tianjin 300222,China [3]Tianjin International Joint Research and Development Center of Low-Carbon Green Process Equipment,Tianjin 300222,China

出　　处：《Building Simulation》2021年第3期535-547,共13页建筑模拟（英文）

基　　金：supported by the National Natural Science Foundation of China(No.51778416);the Key Projects of Philosophy and Social Sciences Research,Ministry of Education of China“Research on Green Design in Sustainable Development”(contract No.16JZDH014,approval No.16JZD014).

摘　　要：Global urbanization causes more environmental stresses in cities and energy efficiency is one of major concerns for urban sustainability.The variable importance techniques have been widely used in building energy analysis to determine key factors influencing building energy use.Most of these applications,however,use only one type of variable importance approaches.Therefore,this paper proposes a procedure of conducting two types of variable importance analysis(predictive and variance-based)to determine robust and effective energy saving measures in urban buildings.These two variable importance methods belong to metamodeling techniques,which can significantly reduce computational cost of building energy simulation models for urban buildings.The predictive importance analysis is based on the prediction errors of metamodels to obtain importance rankings of inputs,while the variance-based variable importance can explore non-linear effects and interactions among input variables based on variance decomposition.The campus buildings are used to demonstrate the application of the method proposed to explore characteristic of heating energy,cooling energy,electricity,and carbon emissions of buildings.The results indicate that the combination of two types of metamodeling variable importance analysis can provide fast and robust analysis to improve energy efficiency of urban buildings.The carbon emissions can be reduced approximately 30%after using a few of effective energy efficiency measures and more aggressive measures can lead to the 60%of reduction of carbon emissions.Moreover,this research demonstrates the application of parallel computing to expedite building energy analysis in urban environment since more multi-core computers become increasingly available.

关 键 词：urban buildings variable importance METAMODELING energy performance carbon emissions 

分 类 号：TU111.195[建筑科学—建筑理论]