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      ENERGY ASSESSMENT OF URBAN BUILDINGS BASED ON GEOGRAPHIC INFORMATION SYSTEM

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          ABSTRACT

          Urban building energy analysis has attracted more attention as the population living in cities increases as does the associated energy consumption in urban environments. This paper proposes a systematic bottom-up method to conduct energy analysis and assess energy saving potentials by combining dynamic engineering-based energy models, machine learning models, and global sensitivity analysis within the GIS (Geographic Information System) environment for large-scale urban buildings. This method includes five steps: database construction of building parameters, automation of creating building models at the GIS environment, construction of machine learning models for building energy assessment, sensitivity analysis for choosing energy saving measures, and GIS visual evaluation of energy saving schemes. Campus buildings in Tianjin (China) are used as a case study to demonstrate the application of the method proposed in this research. The results indicate that the method proposed here can provide reliable and fast analysis to evaluate the energy performance of urban buildings and determine effective energy saving measures to reduce energy consumption of urban buildings. Moreover, the GIS-based analysis is very useful to both create energy models of buildings and display energy analysis results for urban buildings.

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          Most cited references 30

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          A review of sensitivity analysis methods in building energy analysis

           Wei Tian (2013)
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            EasyABC: performing efficient approximate Bayesian computation sampling schemes using R

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              Making BUGS open

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                Author and article information

                Journal
                jgrb
                College Publishing
                Journal of Green Building
                College Publishing
                1943-4618
                1552-6100
                Summer 2020
                21 September 2020
                : 15
                : 3
                : 83-93
                Author notes

                1. College of Mechanical Engineering, Tianjin University of Science and Technology, Tianjin, China, 300222

                2. Tianjin International Joint Research and Development Center of Low-Carbon Green Process Equipment, Tianjin 300222, China

                3. School of Mechanical Engineering, Tongji University, Shanghai, China, 200092

                4. Tianjin Architecture Design Institute, Tianjin, China, 300074

                (*Corresponding email: tjtianjin@ 123456126.com )
                Article
                10.3992/jgb.15.3.83
                © 2020 by College Publishing. All rights reserved.

                Volumes 1-10 of JOGB are open access and do not require permission for use, though proper citation should be given. To view the licenses, visit https://creativecommons.org/licenses/by-nc/4.0/

                Page count
                Pages: 12
                Product
                Categories
                RESEARCH ARTICLES

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