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Title: Modeling urban building energy use: A review of modeling approaches and procedures

Abstract

With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration.

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1422326
Report Number(s):
PNNL-SA-129914
Journal ID: ISSN 0360-5442; KP1601050
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Energy (Oxford); Journal Volume: 141; Journal Issue: C
Country of Publication:
United States
Language:
English
Subject:
Urban building energy use; Top-down approaches; Bottom-up approaches; Energy modeling

Citation Formats

Li, Wenliang, Zhou, Yuyu, Cetin, Kristen, Eom, Jiyong, Wang, Yu, Chen, Gang, and Zhang, Xuesong. Modeling urban building energy use: A review of modeling approaches and procedures. United States: N. p., 2017. Web. doi:10.1016/j.energy.2017.11.071.
Li, Wenliang, Zhou, Yuyu, Cetin, Kristen, Eom, Jiyong, Wang, Yu, Chen, Gang, & Zhang, Xuesong. Modeling urban building energy use: A review of modeling approaches and procedures. United States. doi:10.1016/j.energy.2017.11.071.
Li, Wenliang, Zhou, Yuyu, Cetin, Kristen, Eom, Jiyong, Wang, Yu, Chen, Gang, and Zhang, Xuesong. Fri . "Modeling urban building energy use: A review of modeling approaches and procedures". United States. doi:10.1016/j.energy.2017.11.071.
@article{osti_1422326,
title = {Modeling urban building energy use: A review of modeling approaches and procedures},
author = {Li, Wenliang and Zhou, Yuyu and Cetin, Kristen and Eom, Jiyong and Wang, Yu and Chen, Gang and Zhang, Xuesong},
abstractNote = {With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration.},
doi = {10.1016/j.energy.2017.11.071},
journal = {Energy (Oxford)},
number = C,
volume = 141,
place = {United States},
year = {Fri Dec 01 00:00:00 EST 2017},
month = {Fri Dec 01 00:00:00 EST 2017}
}