An inquiry into the capabilities of baseline building energy modelling approaches to estimate energy savings

Afroz, Z; Burak Gunay, H; O'Brien, W; Newsham, G; Wilton, I

An inquiry into the capabilities of baseline building energy modelling approaches to estimate energy savings

Afroz, Z

Burak Gunay, H O'Brien, W Newsham, G Wilton, I

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: Energy and Buildings, 2021, 244, pp. 111054-111054
Issue Date:: 2021-08-01

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Field	Value	Language
dc.contributor.author	Afroz, Z https://orcid.org/0000-0002-4053-108X
dc.contributor.author	Burak Gunay, H
dc.contributor.author	O'Brien, W
dc.contributor.author	Newsham, G
dc.contributor.author	Wilton, I
dc.date.accessioned	2021-11-29T05:37:34Z
dc.date.available	2021-11-29T05:37:34Z
dc.date.issued	2021-08-01
dc.identifier.citation	Energy and Buildings, 2021, 244, pp. 111054-111054
dc.identifier.issn	0378-7788
dc.identifier.uri	http://hdl.handle.net/10453/151906
dc.description.abstract	While baseline energy modelling approaches for buildings are progressing to meet the demand for measurement and verification (M&V) of savings of an energy performance contract, more robust and insightful modelling approaches are needed. This study compares four baseline modelling approaches (e.g., change point, nonlinear autoregressive exogenous models (NARX), Gaussian process, and ensembles of trees) in terms of predictive accuracy and operational insights. The approaches were selected based on preliminary study and employed on pre- and post-intervention data gathered from twelve commercial buildings in Ottawa, Canada. Changes in the post-intervention energy use were estimated by comparing the predicted data with measured data for the individual buildings. The known primary intervention in these buildings was implementing commercially available smart building technologies that identify and address operational suboptimalities. A deeper analysis of one building's automation system data indicates that energy savings were largely due to simple corrective actions such as eliminating the concurrent operation of heating and cooling coils of an air handling unit. The results show that saving estimates are largely affected by the choice of baseline energy modelling approach. NARX outperformed all other modelling approaches regarding accuracy and data fitting capability. On the contrary, the change point modelling approach offered insights into the operational performance of the buildings.
dc.language	en
dc.publisher	Elsevier BV
dc.relation.ispartof	Energy and Buildings
dc.relation.isbasedon	10.1016/j.enbuild.2021.111054
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	09 Engineering, 12 Built Environment and Design
dc.subject.classification	Building & Construction
dc.title	An inquiry into the capabilities of baseline building energy modelling approaches to estimate energy savings
dc.type	Journal Article
utslib.citation.volume	244
utslib.for	09 Engineering
utslib.for	12 Built Environment and Design
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building/School of Built Environment
utslib.copyright.status	closed_access	*
dc.date.updated	2021-11-29T05:37:31Z
pubs.publication-status	Published
pubs.volume	244

Abstract:

While baseline energy modelling approaches for buildings are progressing to meet the demand for measurement and verification (M&V) of savings of an energy performance contract, more robust and insightful modelling approaches are needed. This study compares four baseline modelling approaches (e.g., change point, nonlinear autoregressive exogenous models (NARX), Gaussian process, and ensembles of trees) in terms of predictive accuracy and operational insights. The approaches were selected based on preliminary study and employed on pre- and post-intervention data gathered from twelve commercial buildings in Ottawa, Canada. Changes in the post-intervention energy use were estimated by comparing the predicted data with measured data for the individual buildings. The known primary intervention in these buildings was implementing commercially available smart building technologies that identify and address operational suboptimalities. A deeper analysis of one building's automation system data indicates that energy savings were largely due to simple corrective actions such as eliminating the concurrent operation of heating and cooling coils of an air handling unit. The results show that saving estimates are largely affected by the choice of baseline energy modelling approach. NARX outperformed all other modelling approaches regarding accuracy and data fitting capability. On the contrary, the change point modelling approach offered insights into the operational performance of the buildings.

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http://hdl.handle.net/10453/151906