Energy and carbon performance of urban buildings using metamodeling variable importance techniques
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Energy and carbon performance of urban buildings using metamodeling variable importance techniques
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
Abstract
Keywords
Global urbanization causes more environmental stresses in cities and energy efficiency is one of
urban buildings,
major concerns for urban sustainability. The variable importance techniques have been widely
variable importance,
used in building energy analysis to determine key factors influencing building energy use. Most of
metamodeling,
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
energy performance,
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
Research Article
Yunliang Liu1, Wei Tian2,3 (), Xiang Zhou1 ()
carbon emissions
Article History Received: 30 November 2019 Revised: 16 June 2020 Accepted: 12 July 2020 © Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020
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.
1
Introduction
In 2018, 55% of total world population live in urban areas and it is projected that 68% of total world population will reside in urban areas by 2050 (UN 2019). Hence, more energy use would be expected in urban areas, especially increasing building energy use to maintain thermal comfort in buildings. Therefore, it is necessary to thoroughly assess urban building energy efficiency and implement effective energy efficiency measures in order to reduce energy use and associated carbon emissions in urban environments (Chen et al. 2019b;
Muñoz et al. 2
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