Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis

Chen, Yixing; Hong, Tianzhen; Piette, Mary Ann

doi:10.1016/j.apenergy.2017.07.128

Title: Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis

Journal Article · Mon Aug 07 00:00:00 EDT 2017 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2017.07.128· OSTI ID:1436612

Chen, Yixing ^[1];

^[1]; Piette, Mary Ann ^[1]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Buildings in cities consume 30–70% of total primary energy, and improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures (ECMs) for investment and the design of incentive and rebate programs. This paper presents the retrofit analysis feature of City Building Energy Saver (CityBES) to automatically generate and simulate UBEM using EnergyPlus based on cities’ building datasets and user-selected ECMs. CityBES is a new open web-based tool to support city-scale building energy efficiency strategic plans and programs. The technical details of using CityBES for UBEM generation and simulation are introduced, including the workflow, key assumptions, and major databases. Also presented is a case study that analyzes the potential retrofit energy use and energy cost savings of five individual ECMs and two measure packages for 940 office and retail buildings in six city districts in northeast San Francisco, United States. The results show that: (1) all five measures together can save 23–38% of site energy per building; (2) replacing lighting with light-emitting diode lamps and adding air economizers to existing heating, ventilation and air-conditioning (HVAC) systems are most cost-effective with an average payback of 2.0 and 4.3 years, respectively; and (3) it is not economical to upgrade HVAC systems or replace windows in San Francisco due to the city's mild climate and minimal cooling and heating loads. Furthermore, the CityBES retrofit analysis feature does not require users to have deep knowledge of building systems or technologies for the generation and simulation of building energy models, which helps overcome major technical barriers for city managers and their consultants to adopt UBEM.

View Accepted Manuscript (DOE)

View Accepted Manuscript (Publisher)

Cite

Export

Save

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1436612

Alternate ID(s):: OSTI ID: 1549851

Journal Information:: Applied Energy, Vol. 205, Issue C; ISSN 0306-2619

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 216 works

Citation information provided by
Web of Science

References (19)

World Urbanization Prospects: an alternative to the UN model of projection compatible with the mobility transition theory Bocquier, Philippe Demographic Research, Vol. 12 https://doi.org/10.4054/DemRes.2005.12.9	journal	January 2005
Estimation of the building energy use intensity in the urban scale by integrating GIS and big data technology Ma, Jun; Cheng, Jack C. P. Applied Energy, Vol. 183 https://doi.org/10.1016/j.apenergy.2016.08.079	journal	December 2016
A data-driven predictive model of city-scale energy use in buildings Kontokosta, Constantine E.; Tull, Christopher Applied Energy, Vol. 197 https://doi.org/10.1016/j.apenergy.2017.04.005	journal	July 2017
Urban building energy modeling – A review of a nascent field Reinhart, Christoph F.; Cerezo Davila, Carlos Building and Environment, Vol. 97 https://doi.org/10.1016/j.buildenv.2015.12.001	journal	February 2016
Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts Fonseca, Jimeno A.; Schlueter, Arno Applied Energy, Vol. 142 https://doi.org/10.1016/j.apenergy.2014.12.068	journal	March 2015
Modeling Boston: A workflow for the efficient generation and maintenance of urban building energy models from existing geospatial datasets Cerezo Davila, Carlos; Reinhart, Christoph F.; Bemis, Jamie L. Energy, Vol. 117 https://doi.org/10.1016/j.energy.2016.10.057	journal	December 2016
Energy performance assessment in urban planning competitions Eicker, Ursula; Monien, Dirk; Duminil, Éric Applied Energy, Vol. 155 https://doi.org/10.1016/j.apenergy.2015.05.094	journal	October 2015
Outdoor thermal environment for different urban forms under summer conditions Xuan, Yingli; Yang, Guang; Li, Qiong Building Simulation, Vol. 9, Issue 3 https://doi.org/10.1007/s12273-016-0274-7	journal	January 2016
Commercial Building Energy Saver: An energy retrofit analysis toolkit Hong, Tianzhen; Piette, Mary Ann; Chen, Yixing Applied Energy, Vol. 159 https://doi.org/10.1016/j.apenergy.2015.09.002	journal	December 2015
Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance Lee, Sang Hoon; Hong, Tianzhen; Piette, Mary Ann Energy, Vol. 90 https://doi.org/10.1016/j.energy.2015.07.107	journal	October 2015
Spatial clustering for district heating integration in urban energy systems: Application to geothermal energy Unternährer, Jérémy; Moret, Stefano; Joost, Stéphane Applied Energy, Vol. 190 https://doi.org/10.1016/j.apenergy.2016.12.136	journal	March 2017
Complex networks for the integration of distributed energy systems in urban areas Fichera, Alberto; Frasca, Mattia; Volpe, Rosaria Applied Energy, Vol. 193 https://doi.org/10.1016/j.apenergy.2017.02.065	journal	May 2017
A pattern-based automated approach to building energy model calibration Sun, Kaiyu; Hong, Tianzhen; Taylor-Lange, Sarah C. Applied Energy, Vol. 165 https://doi.org/10.1016/j.apenergy.2015.12.026	journal	March 2016
The significance of using local predicted temperature for cooling load simulation in the tropics Ignatius, Marcel; Wong, Nyuk Hien; Jusuf, Steve Kardinal Energy and Buildings, Vol. 118 https://doi.org/10.1016/j.enbuild.2016.02.043	journal	April 2016
Evaluation of the impact of the surrounding urban morphology on building energy consumption Wong, Nyuk Hien; Jusuf, Steve Kardinal; Syafii, Nedyomukti Imam Solar Energy, Vol. 85, Issue 1 https://doi.org/10.1016/j.solener.2010.11.002	journal	January 2011
Numerical Evaluation of the Local Weather Data Impacts on Cooling Energy Use of Buildings in an Urban Area Liu, Jiying; Heidarinejad, Mohammad; Guo, Min Procedia Engineering, Vol. 121 https://doi.org/10.1016/j.proeng.2015.08.1082	journal	January 2015
Effect of urban neighborhoods on the performance of building cooling systems Gracik, Stefan; Heidarinejad, Mohammad; Liu, Jiying Building and Environment, Vol. 90 https://doi.org/10.1016/j.buildenv.2015.02.037	journal	August 2015
Cooling and energy saving potentials of shade trees and urban lawns in a desert city Wang, Zhi-Hua; Zhao, Xiaoxi; Yang, Jiachuan Applied Energy, Vol. 161 https://doi.org/10.1016/j.apenergy.2015.10.047	journal	January 2016
A city scale degree-day method to assess building space heating energy demands in Strasbourg Eurometropolis (France) Kohler, M.; Blond, N.; Clappier, A. Applied Energy, Vol. 184 https://doi.org/10.1016/j.apenergy.2016.09.075	journal	December 2016

Cited By (10)

A methodology for auto-calibrating urban building energy models using surrogate modeling techniques Nagpal, Shreshth; Mueller, Caitlin; Aijazi, Arfa Journal of Building Performance Simulation, Vol. 12, Issue 1 https://doi.org/10.1080/19401493.2018.1457722	journal	April 2018
An energy-saving retrofit baseline determination method for large-scale building based on investigation data Zheng, Donglin; Yu, Lijun; Wang, Lizhen Science and Technology for the Built Environment, Vol. 25, Issue 4 https://doi.org/10.1080/23744731.2018.1535215	journal	January 2019
Planning for sustainable cities by estimating building occupancy with mobile phones Barbour, Edward; Davila, Carlos Cerezo; Gupta, Siddharth Nature Communications, Vol. 10, Issue 1 https://doi.org/10.1038/s41467-019-11685-w	journal	August 2019
A Data Ecosystem for Data-Driven Thermal Energy Transition: Reflection on Current Practice and Suggestions for Re-Design Diran, Devin; Hoppe, Thomas; Ubacht, Jolien Energies, Vol. 13, Issue 2 https://doi.org/10.3390/en13020444	journal	January 2020
Building simulation: Ten challenges Hong, Tianzhen; Langevin, Jared; Sun, Kaiyu Building Simulation, Vol. 11, Issue 5 https://doi.org/10.1007/s12273-018-0444-x	journal	April 2018
An Approach to Study District Thermal Flexibility Using Generative Modeling from Existing Data Pajot, Camille; Artiges, Nils; Delinchant, Benoit Energies, Vol. 12, Issue 19 https://doi.org/10.3390/en12193632	journal	September 2019
Energy Pathways for Future Residential Building Areas in Norway Nord, Natasa; Skrautvol, Ola; Eliassen, Stian Fossmo Springer Proceedings in Energy https://doi.org/10.1007/978-3-030-00662-4_42	book	December 2018
An Open Source Modeling Framework for Interdependent Energy-Transportation- Communication Infrastructure in Smart and Connected Communities Lu, Xing; Hinkelman, Kathryn; Fu, Yangyang arXiv https://doi.org/10.48550/arxiv.1904.03678	preprint	January 2019
Life Cycle Assessment of Technical Building Services of Large Residential Building Stocks Using Semantic 3d city Models Harter, H.; Willenborg, B.; Lang, W. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. VI-4/W1-2020 https://doi.org/10.5194/isprs-annals-vi-4-w1-2020-85-2020	journal	September 2020
Geospatial data for Energy Efficiency and low Carbon Cities – Overview, Experiences and new Perspectives – Nowacka, A.; Remondino, F. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLII-4 https://doi.org/10.5194/isprs-archives-xlii-4-467-2018	journal	September 2018

Similar Records

Modeling City Building Stock for Large-Scale Energy Efficiency Improvements using CityBES

Conference · Tue Sep 18 00:00:00 EDT 2018 · OSTI ID:1436612

Hong, Tianzhen; Chen, Yixing; Piette, Mary Ann; +1 more

Development of city buildings dataset for urban building energy modeling

Journal Article · Sat Nov 17 00:00:00 EST 2018 · Energy and Buildings · OSTI ID:1436612

Chen, Yixing; Hong, Tianzhen; Luo, Xuan; +1 more

Energy-Efficient and Comfortable Buildings through Multivariate Integrated Control (ECoMIC)

Technical Report · Mon Oct 28 00:00:00 EDT 2013 · OSTI ID:1436612

Birru, Dagnachew; Wen, Yao-Jung; Rubinstein, Francis M.; +1 more

Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
CityBES
Urban scale
Building energy modeling
EnergyPlus
Energy conservation measures
Retrofit analysis

Title: Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis

Citation Formats

References (19)

Cited By (10)

Similar Records

Related Subjects