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

被引:25
作者
Kong, Dezhou [1 ]
Cheshmehzangi, Ali [2 ,3 ]
Zhang, Zhiang [1 ]
Ardakani, Saeid Pourroostaei [4 ]
Gu, Tingyue [1 ]
机构
[1] Univ Nottingham Ningbo China, Dept Architecture & Built Environm, Ningbo, Peoples R China
[2] Qingdao City Univ, Sch Architecture, Qingdao, Peoples R China
[3] Hiroshima Univ, Network Educ & Res Peace & Sustainabil NERPS, Hiroshima, Japan
[4] Univ Lincoln, Sch Comp Sci, Lincoln, England
关键词
Urban building energy modeling(UBEM); Systematic review; Energy simulations; Urban scale; Top-down; Bottom-up; SENSITIVITY-ANALYSIS; DECISION-MAKING; OCCUPANT BEHAVIOR; RETROFIT ANALYSIS; SIMULATION; STOCK; UNCERTAINTY; CONSUMPTION; PERFORMANCE; CALIBRATION;
D O I
10.1007/s12053-023-10147-z
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
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.
引用
收藏
页数:42
相关论文
共 178 条
[51]   Uncertainty in peak cooling load calculations [J].
Dominguez-Munoz, Fernando ;
Cejudo-Lopez, Jose M. ;
Carrillo-Andres, Antonio .
ENERGY AND BUILDINGS, 2010, 42 (07) :1010-1018
[52]  
Dorer V, 2013, BUILDING SIMULATION 2013: 13TH INTERNATIONAL CONFERENCE OF THE INTERNATIONAL BUILDING PERFORMANCE SIMULATION ASSOCIATION, P3483
[53]  
Energy D, 2001, HDB FINANCING ENERGY, P249
[54]  
ESRI, 1998, SHAP TECHN DESCR
[55]   Developing archetypes for domestic dwellings-An Irish case study [J].
Famuyibo, Adesoji Albert ;
Duffy, Aidan ;
Strachan, Paul .
ENERGY AND BUILDINGS, 2012, 50 :150-157
[56]   Improving cooling load prediction reliability for HVAC system using Monte-Carlo simulation to deal with uncertainties in input variables [J].
Fan, Chengliang ;
Liao, Yundan ;
Zhou, Guang ;
Zhou, Xiaoqing ;
Ding, Yunfei .
ENERGY AND BUILDINGS, 2020, 226
[57]   Machine learning applications in urban building energy performance forecasting: A systematic review [J].
Fathi, Soheil ;
Srinivasan, Ravi ;
Fenner, Andriel ;
Fathi, Sahand .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2020, 133
[58]   Energy impact of the air infiltration in residential buildings in the Mediterranean area of Spain and the Canary islands [J].
Feijo-Munoz, Jesus ;
Pardal, Cristina ;
Echarri, Victor ;
Fernandez-Aguera, Jesica ;
Assiego de Larriva, Rafael ;
Montesdeoca Calderin, Manuel ;
Poza-Casado, Irene ;
Angel Padilla-Marcos, Miguel ;
Meiss, Alberto .
ENERGY AND BUILDINGS, 2019, 188 :226-238
[59]   Urban building energy modeling (UBEM) tools: A state-of-the-art review of bottom-up physics-based approaches [J].
Ferrando, Martina ;
Causone, Francesco ;
Hong, Tianzhen ;
Chen, Yixing .
SUSTAINABLE CITIES AND SOCIETY, 2020, 62
[60]  
Fonseca JA, 2016, EXPANDING BOUNDARIES: SYSTEMS THINKING IN THE BUILT ENVIRONMENT, P584