Improving the accuracy of energy baseline models for commercial buildings with occupancy data
Abstract
More than 80% of energy is consumed during operation phase of a building's life cycle, so energy efficiency retrofit for existing buildings is considered a promising way to reduce energy use in buildings. The investment strategies of retrofit depend on the ability to quantify energy savings by “measurement and verification” (M&V), which compares actual energy consumption to how much energy would have been used without retrofit (called the “baseline” of energy use). Although numerous models exist for predicting baseline of energy use, a critical limitation is that occupancy has not been included as a variable. However, occupancy rate is essential for energy consumption and was emphasized by previous studies. This study develops a new baseline model which is built upon the Lawrence Berkeley National Laboratory (LBNL) model but includes the use of building occupancy data. The study also proposes metrics to quantify the accuracy of prediction and the impacts of variables. However, the results show that including occupancy data does not significantly improve the accuracy of the baseline model, especially for HVAC load. The reasons are discussed further. In addition, sensitivity analysis is conducted to show the influence of parameters in baseline models. To conclude, the results from this studymore »
- Authors:
-
- Shanghai Jiao Tong Univ. (China). School of International and Public Affairs; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Building Technology and Urban Systems Division
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Building Technology and Urban Systems Division
- Hong Kong Polytechnic Univ. (China). Dept. of Building and Real Estate
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE); National Natural Science Foundation of China (NSFC); Hong Kong Polytechnic Univ. (China); Rutgers Univ., Piscataway, NJ (United States); International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66
- OSTI Identifier:
- 1436599
- Alternate Identifier(s):
- OSTI ID: 1399815
- Grant/Contract Number:
- AC02-05CH11231; 71271184
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- Applied Energy
- Additional Journal Information:
- Journal Volume: 179; Journal Issue: C; Journal ID: ISSN 0306-2619
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 29 ENERGY PLANNING, POLICY, AND ECONOMY; Baseline model; Occupancy; Building energy use; Measurement and verification; Energy efficiency retrofit
Citation Formats
Liang, Xin, Hong, Tianzhen, and Shen, Geoffrey Qiping. Improving the accuracy of energy baseline models for commercial buildings with occupancy data. United States: N. p., 2016.
Web. doi:10.1016/j.apenergy.2016.06.141.
Liang, Xin, Hong, Tianzhen, & Shen, Geoffrey Qiping. Improving the accuracy of energy baseline models for commercial buildings with occupancy data. United States. https://doi.org/10.1016/j.apenergy.2016.06.141
Liang, Xin, Hong, Tianzhen, and Shen, Geoffrey Qiping. 2016.
"Improving the accuracy of energy baseline models for commercial buildings with occupancy data". United States. https://doi.org/10.1016/j.apenergy.2016.06.141. https://www.osti.gov/servlets/purl/1436599.
@article{osti_1436599,
title = {Improving the accuracy of energy baseline models for commercial buildings with occupancy data},
author = {Liang, Xin and Hong, Tianzhen and Shen, Geoffrey Qiping},
abstractNote = {More than 80% of energy is consumed during operation phase of a building's life cycle, so energy efficiency retrofit for existing buildings is considered a promising way to reduce energy use in buildings. The investment strategies of retrofit depend on the ability to quantify energy savings by “measurement and verification” (M&V), which compares actual energy consumption to how much energy would have been used without retrofit (called the “baseline” of energy use). Although numerous models exist for predicting baseline of energy use, a critical limitation is that occupancy has not been included as a variable. However, occupancy rate is essential for energy consumption and was emphasized by previous studies. This study develops a new baseline model which is built upon the Lawrence Berkeley National Laboratory (LBNL) model but includes the use of building occupancy data. The study also proposes metrics to quantify the accuracy of prediction and the impacts of variables. However, the results show that including occupancy data does not significantly improve the accuracy of the baseline model, especially for HVAC load. The reasons are discussed further. In addition, sensitivity analysis is conducted to show the influence of parameters in baseline models. To conclude, the results from this study can help us understand the influence of occupancy on energy use, improve energy baseline prediction by including the occupancy factor, reduce risks of M&V and facilitate investment strategies of energy efficiency retrofit.},
doi = {10.1016/j.apenergy.2016.06.141},
url = {https://www.osti.gov/biblio/1436599},
journal = {Applied Energy},
issn = {0306-2619},
number = C,
volume = 179,
place = {United States},
year = {Thu Jul 07 00:00:00 EDT 2016},
month = {Thu Jul 07 00:00:00 EDT 2016}
}
Web of Science
Works referenced in this record:
Success factors of energy performance contracting (EPC) for sustainable building energy efficiency retrofit (BEER) of hotel buildings in China
journal, November 2011
- Xu, Pengpeng; Chan, Edwin Hon-Wan; Qian, Queena Kun
- Energy Policy, Vol. 39, Issue 11
Greenhouse gas emissions during the construction phase of a building: a case study in China
journal, September 2015
- Hong, Jingke; Shen, Geoffrey Qiping; Feng, Yong
- Journal of Cleaner Production, Vol. 103
A framework to assess the role of stakeholders in sustainable building retrofit decisions
journal, February 2014
- Menassa, Carol C.; Baer, Brad
- Sustainable Cities and Society, Vol. 10
Commercial Building Energy Saver: An energy retrofit analysis toolkit
journal, December 2015
- Hong, Tianzhen; Piette, Mary Ann; Chen, Yixing
- Applied Energy, Vol. 159
Uncertainty estimation improves energy measurement and verification procedures
journal, October 2014
- Walter, Travis; Price, Phillip N.; Sohn, Michael D.
- Applied Energy, Vol. 130
ANP model for sustainable Building Energy Efficiency Retrofit (BEER) using Energy Performance Contracting (EPC) for hotel buildings in China
journal, January 2013
- Xu, Pengpeng; Chan, Edwin H. W.
- Habitat International, Vol. 37
Mathematical description for the measurement and verification of energy efficiency improvement
journal, November 2013
- Xia, Xiaohua; Zhang, Jiangfeng
- Applied Energy, Vol. 111
Variability in automated responses of commercial buildings and industrial facilities to dynamic electricity prices
journal, December 2011
- Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila
- Energy and Buildings, Vol. 43, Issue 12
Statistical analysis of baseline load models for non-residential buildings
journal, April 2009
- Coughlin, Katie; Piette, Mary Ann; Goldman, Charles
- Energy and Buildings, Vol. 41, Issue 4
Automated measurement and verification: Performance of public domain whole-building electric baseline models
journal, April 2015
- Granderson, Jessica; Price, Phillip N.; Jump, David
- Applied Energy, Vol. 144
Development and application of a statistical methodology to evaluate the predictive accuracy of building energy baseline models
journal, March 2014
- Granderson, Jessica; Price, Phillip N.
- Energy, Vol. 66
A Perspective on Methods for Analysis of Measured Energy Data from Commercial Buildings
journal, August 1998
- Claridge, D. E.
- Journal of Solar Energy Engineering, Vol. 120, Issue 3
A comparison of univariate methods for forecasting electricity demand up to a day ahead
journal, January 2006
- Taylor, James W.; de Menezes, Lilian M.; McSharry, Patrick E.
- International Journal of Forecasting, Vol. 22, Issue 1
Multivariate Regression Modeling
journal, August 1998
- Katipamula, S.; Reddy, T. A.; Claridge, D. E.
- Journal of Solar Energy Engineering, Vol. 120, Issue 3
Ambient-Temperature Regression Analysis for Estimating Retrofit Savings in Commercial Buildings
journal, August 1998
- Kissock, J. K.; Reddy, T. A.; Claridge, D. E.
- Journal of Solar Energy Engineering, Vol. 120, Issue 3
Benchmarking the energy efficiency of government buildings with data envelopment analysis
journal, January 2008
- Lee, Wen-Shing
- Energy and Buildings, Vol. 40, Issue 5
A study of energy efficiency of private office buildings in Hong Kong
journal, June 2009
- Chung, William; Hui, Y. V.
- Energy and Buildings, Vol. 41, Issue 6
Benchmarking the energy efficiency of commercial buildings
journal, January 2006
- Chung, William; Hui, Y. V.; Lam, Y. Miu
- Applied Energy, Vol. 83, Issue 1
Energy efficiency benchmarks and the performance of LEED rated buildings for Information Technology facilities in Bangalore, India
journal, November 2010
- Sabapathy, Ashwin; Ragavan, Santhosh K. V.; Vijendra, Mahima
- Energy and Buildings, Vol. 42, Issue 11
ENERNET: Studying the dynamic relationship between building occupancy and energy consumption
journal, April 2012
- Martani, Claudio; Lee, David; Robinson, Prudence
- Energy and Buildings, Vol. 47
Measuring and monitoring occupancy with an RFID based system for demand-driven HVAC operations
journal, July 2012
- Li, Nan; Calis, Gulben; Becerik-Gerber, Burcin
- Automation in Construction, Vol. 24
Human-based energy retrofits in residential buildings: A cost-effective alternative to traditional physical strategies
journal, November 2014
- Pisello, Anna Laura; Asdrubali, Francesco
- Applied Energy, Vol. 133
Importance of occupancy information for building climate control
journal, January 2013
- Oldewurtel, Frauke; Sturzenegger, David; Morari, Manfred
- Applied Energy, Vol. 101
Simulation of occupancy in buildings
journal, January 2015
- Feng, Xiaohang; Yan, Da; Hong, Tianzhen
- Energy and Buildings, Vol. 87
Advances in research and applications of energy-related occupant behavior in buildings
journal, March 2016
- Hong, Tianzhen; Taylor-Lange, Sarah C.; D’Oca, Simona
- Energy and Buildings, Vol. 116
Occupant behavior modeling for building performance simulation: Current state and future challenges
journal, November 2015
- Yan, Da; O’Brien, William; Hong, Tianzhen
- Energy and Buildings, Vol. 107
Office building retrofitting strategies: multicriteria approach of an architectural and technical issue
journal, April 2004
- Rey, Emmanuel
- Energy and Buildings, Vol. 36, Issue 4
Optimization of an envelope retrofit strategy for an existing office building
journal, December 2012
- Güçyeter, Başak; Günaydın, H. Murat
- Energy and Buildings, Vol. 55
Retrofitting commercial office buildings for sustainability: tenants' perspectives
journal, September 2008
- Miller, Evonne; Buys, Laurie
- Journal of Property Investment & Finance, Vol. 26, Issue 6
Does Green Pay Off?
journal, January 2008
- Miller, Norm; Spivey, Jay; Florance, Andrew
- Journal of Real Estate Portfolio Management, Vol. 14, Issue 4
Green Design and the Market for Commercial Office Space
journal, July 2008
- Wiley, Jonathan A.; Benefield, Justin D.; Johnson, Ken H.
- The Journal of Real Estate Finance and Economics, Vol. 41, Issue 2
Data analysis and stochastic modeling of lighting energy use in large office buildings in China
journal, January 2015
- Zhou, Xin; Yan, Da; Hong, Tianzhen
- Energy and Buildings, Vol. 86
Stochastic modeling of overtime occupancy and its application in building energy simulation and calibration
journal, September 2014
- Sun, Kaiyu; Yan, Da; Hong, Tianzhen
- Building and Environment, Vol. 79
Works referencing / citing this record:
Progressing sustainable development of “the Belt and Road countries”: Estimating environmental efficiency based on the Super‐slack‐based measure model
journal, December 2019
- Wei, Yigang; Li, Yan; Wu, Meiyu
- Sustainable Development, Vol. 28, Issue 4
Sustainable development and green gross domestic product assessments in megacities based on the emergy analysis method—A case study of Wuhan
journal, June 2019
- Wei, Yigang; Li, Yan; Liu, Xinjing
- Sustainable Development, Vol. 28, Issue 1
An energy-saving retrofit baseline determination method for large-scale building based on investigation data
journal, January 2019
- Zheng, Donglin; Yu, Lijun; Wang, Lizhen
- Science and Technology for the Built Environment, Vol. 25, Issue 4
Deep Learning in Modeling Energy Cost of Buildings in the Public Sector
book, May 2019
- Zekić-Sušac, Marijana; Knežević, Marinela; Scitovski, Rudolf
- 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019): Seville, Spain, May 13–15, 2019, Proceedings, p. 101-110
Building simulation: Ten challenges
journal, April 2018
- Hong, Tianzhen; Langevin, Jared; Sun, Kaiyu
- Building Simulation, Vol. 11, Issue 5
On the quality evaluation of behavioural models for building performance applications
journal, September 2016
- Mahdavi, Ardeshir; Tahmasebi, Farhang
- Journal of Building Performance Simulation, Vol. 10, Issue 5-6