Urban building energy modeling (UBEM): a systematic review of challenges and opportunities

被引:0
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作者
Dezhou Kong
Ali Cheshmehzangi
Zhiang Zhang
Saeid Pourroostaei Ardakani
Tingyue Gu
机构
[1] University of Nottingham Ningbo China,Department of Architecture and Built Environment
[2] Qingdao City University,School of Architecture
[3] Hiroshima University,Network for Education and Research for Peace and Sustainability (NERPS)
[4] University of Lincoln,School of Computer Science
来源
Energy Efficiency | 2023年 / 16卷
关键词
Urban building energy modeling(UBEM); Systematic review; Energy simulations; Urban scale; Top-down; Bottom-up;
D O I
暂无
中图分类号
学科分类号
摘要
In recent decades, urban energy consumption and carbon emissions have expanded rapidly on a global scale. Building sector, in particular, accounts for approximately 40% of overall energy use. Urban planners and decision-makers have a significant responsibility to achieve sustainable energy and climate objectives. Urban building energy modeling (UBEM) has increased in popularity in recent years as a tool for calculating urban-scale energy use in buildings with limited resources, and that facilitated the formulation of new energy policies. However, published studies of UBEM methodologies and tools lack comprehensive examinations of the potential limitations of research and the prospects of future opportunities. This paper provides a complete conceptual framework for UBEM based on extensive literature reviews and prior researchers’ work. In addition to providing a comprehensive understanding of the various UBEM approaches and tools, future research directions are explored. The results demonstrate that earlier researches did not adequately account for input uncertainty and lacked proper simulation and calibration control for algorithms/models. These challenges not only increased the workload and computational burden of modelers but also diminished the precision of model calculations. In response, this paper provides targeted recommendations for each essential phase of the present UBEM workflow, namely model input, model development, and model calibration, to address these limitations, as well as a comprehensive analysis of future prospects. The main aim of the research is to further UBEM development as a faster, more accurate and multiscale supportive tool and establish a framework for future UBEM methods.
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