A regression-based approach to estimating retrofit savings using the Building Performance Database

Walter, Travis; Sohn, Michael D.

doi:10.1016/j.apenergy.2016.07.087

Title: A regression-based approach to estimating retrofit savings using the Building Performance Database

Journal Article · Mon Jul 25 00:00:00 EDT 2016 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2016.07.087· OSTI ID:1378362

Walter, Travis ^[1]; Sohn, Michael D. ^[2]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Division; Univ. of California, Berkeley, CA (United States). Civil and Environmental Engineering Dept.
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Division

Retrofitting building systems is known to provide cost-effective energy savings. This article addresses how the Building Performance Database is used to help identify potential savings. Currently, prioritizing retrofits and computing their expected energy savings and cost/benefits can be a complicated, costly, and an uncertain effort. Prioritizing retrofits for a portfolio of buildings can be even more difficult if the owner must determine different investment strategies for each of the buildings. Meanwhile, we are seeing greater availability of data on building energy use, characteristics, and equipment. These data provide opportunities for the development of algorithms that link building characteristics and retrofits empirically. In this paper we explore the potential of using such data for predicting the expected energy savings from equipment retrofits for a large number of buildings. We show that building data with statistical algorithms can provide savings estimates when detailed energy audits and physics-based simulations are not cost- or time-feasible. We develop a multivariate linear regression model with numerical predictors (e.g., operating hours, occupant density) and categorical indicator variables (e.g., climate zone, heating system type) to predict energy use intensity. The model quantifies the contribution of building characteristics and systems to energy use, and we use it to infer the expected savings when modifying particular equipment. We verify the model using residual analysis and cross-validation. We demonstrate the retrofit analysis by providing a probabilistic estimate of energy savings for several hypothetical building retrofits. We discuss the ways understanding the risk associated with retrofit investments can inform decision making. The contributions of this work are the development of a statistical model for estimating energy savings, its application to a large empirical building dataset, and a discussion of its use in informing building retrofit decisions.

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 Science (SC); USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1378362

Alternate ID(s):: OSTI ID: 1396977

Journal Information:: Applied Energy, Vol. 179, Issue C; ISSN 0306-2619

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 65 works

Citation information provided by
Web of Science

References (37)

The Technology Path to Deep Greenhouse Gas Emissions Cuts by 2050: The Pivotal Role of Electricity Williams, James H.; DeBenedictis, Andrew; Ghanadan, Rebecca Science, Vol. 335, Issue 6064 https://doi.org/10.1126/science.1208365	journal	November 2011
Existing building retrofits: Methodology and state-of-the-art Ma, Zhenjun; Cooper, Paul; Daly, Daniel Energy and Buildings, Vol. 55 https://doi.org/10.1016/j.enbuild.2012.08.018	journal	December 2012
Indoor environmental quality benefits of apartment energy retrofits Noris, Federico; Adamkiewicz, Gary; Delp, William W. Building and Environment, Vol. 68 https://doi.org/10.1016/j.buildenv.2013.07.003	journal	October 2013
Impact of energy efficiency measures on the economic value of buildings Popescu, Daniela; Bienert, Sven; Schützenhofer, Christian Applied Energy, Vol. 89, Issue 1 https://doi.org/10.1016/j.apenergy.2011.08.015	journal	January 2012
Quantitative energy performance assessment methods for existing buildings Wang, Shengwei; Yan, Chengchu; Xiao, Fu Energy and Buildings, Vol. 55 https://doi.org/10.1016/j.enbuild.2012.08.037	journal	December 2012
A review on the prediction of building energy consumption Zhao, Hai-xiang; Magoulès, Frédéric Renewable and Sustainable Energy Reviews, Vol. 16, Issue 6 https://doi.org/10.1016/j.rser.2012.02.049	journal	August 2012
Automatic generation of energy conservation measures in buildings using genetic algorithms Siddharth, V.; Ramakrishna, P. V.; Geetha, T. Energy and Buildings, Vol. 43, Issue 10 https://doi.org/10.1016/j.enbuild.2011.06.028	journal	October 2011
Retrofitting residential buildings in hot and arid climates Al-Ragom, F. Energy Conversion and Management, Vol. 44, Issue 14 https://doi.org/10.1016/S0196-8904(02)00256-X	journal	August 2003
Energy retrofit of historical buildings: theoretical and experimental investigations for the modelling of reliable performance scenarios Ascione, Fabrizio; de Rossi, Filippo; Vanoli, Giuseppe Peter Energy and Buildings, Vol. 43, Issue 8 https://doi.org/10.1016/j.enbuild.2011.03.040	journal	August 2011
Energy conservation measures in an institutional building in sub-tropical climate in Australia Rahman, M. M.; Rasul, M. G.; Khan, M. M. K. Applied Energy, Vol. 87, Issue 10 https://doi.org/10.1016/j.apenergy.2010.04.005	journal	October 2010
Passive retrofitting of office buildings to improve their energy performance and indoor environment: the OFFICE project Santamouris, M.; Dascalaki, E. Building and Environment, Vol. 37, Issue 6 https://doi.org/10.1016/S0360-1323(02)00004-5	journal	June 2002
On the potential of retrofitting scenarios for offices Dascalaki, E.; Santamouris, M. Building and Environment, Vol. 37, Issue 6 https://doi.org/10.1016/S0360-1323(02)00002-1	journal	June 2002
Sensitivity analysis of energy performance of office buildings Lam, Joseph C.; Hui, Sam C. M. Building and Environment, Vol. 31, Issue 1 https://doi.org/10.1016/0360-1323(95)00031-3	journal	January 1996
Sensitivity analysis and energy conservation measures implications Lam, Joseph C.; Wan, Kevin K. W.; Yang, Liu Energy Conversion and Management, Vol. 49, Issue 11 https://doi.org/10.1016/j.enconman.2008.05.022	journal	November 2008
Regression analysis of high-rise fully air-conditioned office buildings Lam, Joseph C.; Hui, Sam C. M.; Chan, Apple L. S. Energy and Buildings, Vol. 26, Issue 2 https://doi.org/10.1016/S0378-7788(96)01034-1	journal	January 1997
Multiple regression models for energy use in air-conditioned office buildings in different climates Lam, Joseph C.; Wan, Kevin K. W.; Liu, Dalong Energy Conversion and Management, Vol. 51, Issue 12 https://doi.org/10.1016/j.enconman.2010.06.004	journal	December 2010
A screening methodology for implementing cost effective energy retrofit measures in Canadian office buildings Chidiac, S. E.; Catania, E. J. C.; Morofsky, E. Energy and Buildings, Vol. 43, Issue 2-3 https://doi.org/10.1016/j.enbuild.2010.11.002	journal	February 2011
Effectiveness of single and multiple energy retrofit measures on the energy consumption of office buildings Chidiac, S. E.; Catania, E. J. C.; Morofsky, E. Energy, Vol. 36, Issue 8 https://doi.org/10.1016/j.energy.2011.05.050	journal	August 2011
Optimum building energy retrofits under technical and economic uncertainty Rysanek, A. M.; Choudhary, R. Energy and Buildings, Vol. 57 https://doi.org/10.1016/j.enbuild.2012.10.027	journal	February 2013
Multi-objective optimization for building retrofit strategies: A model and an application Asadi, Ehsan; da Silva, Manuel Gameiro; Antunes, Carlos Henggeler Energy and Buildings, Vol. 44 https://doi.org/10.1016/j.enbuild.2011.10.016	journal	January 2012
A multi-objective optimization model for building retrofit strategies using TRNSYS simulations, GenOpt and MATLAB Asadi, Ehsan; da Silva, Manuel Gameiro; Antunes, Carlos Henggeler Building and Environment, Vol. 56 https://doi.org/10.1016/j.buildenv.2012.04.005	journal	October 2012
A multi-objective decision model for the improvement of energy efficiency in buildings Diakaki, Christina; Grigoroudis, Evangelos; Kabelis, Nikos Energy, Vol. 35, Issue 12 https://doi.org/10.1016/j.energy.2010.05.012	journal	December 2010
Multivariate Regression Modeling Katipamula, S.; Reddy, T. A.; Claridge, D. E. Journal of Solar Energy Engineering, Vol. 120, Issue 3 https://doi.org/10.1115/1.2888067	journal	August 1998
The effect of occupancy and building characteristics on energy use for space and water heating in Dutch residential stock Guerra Santin, Olivia; Itard, Laure; Visscher, Henk Energy and Buildings, Vol. 41, Issue 11 https://doi.org/10.1016/j.enbuild.2009.07.002	journal	November 2009
Estimation model and benchmarks for heating energy consumption of schools and sport facilities in Germany Beusker, Elisabeth; Stoy, Christian; Pollalis, Spiro N. Building and Environment, Vol. 49 https://doi.org/10.1016/j.buildenv.2011.08.006	journal	March 2012
How much information disclosure of building energy performance is necessary? Hsu, David Energy Policy, Vol. 64 https://doi.org/10.1016/j.enpol.2013.08.094	journal	January 2014
Identifying key variables and interactions in statistical models of building energy consumption using regularization Hsu, David Energy, Vol. 83 https://doi.org/10.1016/j.energy.2015.02.008	journal	April 2015
Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior Kavousian, Amir; Rajagopal, Ram; Fischer, Martin Energy, Vol. 55 https://doi.org/10.1016/j.energy.2013.03.086	journal	June 2013
Improving the prediction of UK domestic energy-demand using annual consumption-data Baker, Keith J.; Rylatt, R. Mark Applied Energy, Vol. 85, Issue 6 https://doi.org/10.1016/j.apenergy.2007.09.004	journal	June 2008
Calibration of building energy models for retrofit analysis under uncertainty Heo, Y.; Choudhary, R.; Augenbroe, G. A. Energy and Buildings, Vol. 47 https://doi.org/10.1016/j.enbuild.2011.12.029	journal	April 2012
Evaluation of economically optimal retrofit investment options for energy savings in buildings Kumbaroğlu, Gürkan; Madlener, Reinhard Energy and Buildings, Vol. 49 https://doi.org/10.1016/j.enbuild.2012.02.022	journal	June 2012
Evaluating sustainable retrofits in existing buildings under uncertainty Menassa, Carol C. Energy and Buildings, Vol. 43, Issue 12 https://doi.org/10.1016/j.enbuild.2011.09.030	journal	December 2011
Energy and environmental benefits in public buildings as a result of retrofit actions Ardente, Fulvio; Beccali, Marco; Cellura, Maurizio Renewable and Sustainable Energy Reviews, Vol. 15, Issue 1 https://doi.org/10.1016/j.rser.2010.09.022	journal	January 2011
Calibrating whole building energy models: An evidence-based methodology Raftery, Paul; Keane, Marcus; O’Donnell, James Energy and Buildings, Vol. 43, Issue 9 https://doi.org/10.1016/j.enbuild.2011.05.020	journal	September 2011
Big-data for building energy performance: Lessons from assembling a very large national database of building energy use Mathew, Paul A.; Dunn, Laurel N.; Sohn, Michael D. Applied Energy, Vol. 140 https://doi.org/10.1016/j.apenergy.2014.11.042	journal	February 2015
A systematic procedure to study the influence of occupant behavior on building energy consumption Yu, Zhun; Fung, Benjamin C. M.; Haghighat, Fariborz Energy and Buildings, Vol. 43, Issue 6 https://doi.org/10.1016/j.enbuild.2011.02.002	journal	June 2011
Validation of building energy modeling tools under idealized and realistic conditions Ryan, Emily M.; Sanquist, Thomas F. Energy and Buildings, Vol. 47 https://doi.org/10.1016/j.enbuild.2011.12.020	journal	April 2012

Similar Records

Weatherization Assistant NEAT/MHEA

Software · Thu Nov 04 00:00:00 EDT 2021 · OSTI ID:1378362

Gettings, Michael; Fishbaugher, Mark; Accawi, Gina; +3 more

Retrofit-ability: A supplementary metric to inform energy efficiency policies and programs

Conference · Mon Aug 17 00:00:00 EDT 2020 · OSTI ID:1378362

Wang, Na; Gonzalez Matamoros, Juan C.; Babu, Libu; +1 more

Development and Validation of Algorithms That Analyze Communicating Thermostat Data to Identify Enclosure Retrofit Opportunities

Technical Report · Fri Jul 01 00:00:00 EDT 2022 · OSTI ID:1378362

Zeifman, Michael; Roth, Kurt

Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION

Title: A regression-based approach to estimating retrofit savings using the Building Performance Database

Citation Formats

References (37)

Similar Records

Related Subjects