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On quantifying building performance adaptability to variable occupancy

Title:

On quantifying building performance adaptability to variable occupancy

Ouf, Mohamed M., O'Brien, William and Gunay, Burak (2019) On quantifying building performance adaptability to variable occupancy. Building and Environment . ISSN 03601323 (In Press)

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Official URL: http://dx.doi.org/10.1016/j.buildenv.2019.03.048

Abstract

Most existing and new buildings adapt poorly to variable occupancy, in part due to technical constraints and common operational practice. Although building automation systems and advanced control strategies aim to address this issue by improving adaptability to partial occupancy, no holistic metrics exist to quantify this aspect of building performance. To this end, we present a technology-independent approach to define adaptability as a building performance attribute and introduce metrics to quantify it. These metrics can be used to evaluate how different building technologies and control strategies influence building operations’ adaptability to variable occupancy or estimate their associated energy savings. To demonstrate these metrics, a case study based on simulating a single-story office building was used to compare several control strategies with regards to their effect on improving adaptability. Results showed how the proposed metrics highlighted the additional benefits of these control strategies, especially under low-occupancy scenarios. Performance-based compliance with building energy codes and standards typically assumes full or near full occupancy, which may underestimate the benefits of adaptable building technologies or controls. Therefore, incorporating adaptability metrics in energy codes and operational guidelines would quantify the benefits of adaptable systems, especially under variable occupancy.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Article
Refereed:Yes
Authors:Ouf, Mohamed M. and O'Brien, William and Gunay, Burak
Journal or Publication:Building and Environment
Date:23 March 2019
Funders:
  • Natural Resources Canada (NRCan)
  • Natural Sciences and Engineering Research Council of Canada (NSERC)
Digital Object Identifier (DOI):10.1016/j.buildenv.2019.03.048
Keywords:Occupancy; Adaptability; Benchmarking metrics; Building performance evaluation; Monitoring
ID Code:985159
Deposited By: Michael Biron
Deposited On:08 Apr 2019 18:11
Last Modified:21 Mar 2021 01:00

References:

L. Golden Flexible work schedules: which workers get them?
Am. Behav. Sci., 44 (7) (2001), pp. 1157-1178

I.U. Zeytinoglu, G.B. Cooke, S.L. Mann “Flexibility : whose choice is it anyway? Relat. Ind., 64 (4) (2009), p. 555

National Research Council “National Energy Code of Canada for Buildings 2015.” Ottawa, ON (2015)

ASHRAE “ANSI/ASHRAE Standard 90.1-2016 Energy Standard for Buildings except Low-Rise Residential Buildings.” Atlanta, GA
(2016)

A. Mahdavi, A. Mohammadi, E. Kabir, L. Lambeva “Occupants' operation of lighting and shading systems in office buildings J. Build. Perform. Simul., 1 (September 2014) (2008), pp. 57-65

Z. Yang, B. Becerik-Gerber The coupled effects of personalized occupancy profile based HVAC schedules and room reassignment on building energy use Energy Build., 78 (2014), pp. 113-122

Z. Yang, B. Becerik-Gerber Modeling personalized occupancy profiles for representing long term patterns by using ambient context Build. Environ., 78 (2014), pp. 23-35

B. Abushakra, J.S. Haberl, D.E. Claridge Overview of existing literature on diversity factors and schedules for energy and cooling load calculations ASHRAE Transact., 110 (Part 1) (2004), pp. 164-176

H. Burak Gunay, W. O'Brien, I. Beausoleil-Morrison Development of an occupancy learning algorithm for terminal heating and cooling units Build. Environ., 93 (P2) (2015), pp. 71-85

W. O'Brien and A. Abdelaliem, “Do building energy codes adequately reward buildings that adapt to partial occupancy?,” Sci. Technol. Built Environ.

J. Brandemuehl, Michael J. Braun The impact of demand-controlled and economizer ventilation strategies on energy use in buildings
ASHRAE Transact., 105 (1999)

Z. Nagy, F.Y. Yong, M. Frei, A. Schlueter Occupant centered lighting control for comfort and energy efficient building operation Energy Build., 94 (2015), pp. 100-108

Y. Peng, A. Rysanek, Z. Nagy, A. Schlüter Occupancy learning-based demand-driven cooling control for office spaces Build. Environ., 122 (2017), pp. 145-160

H.B. Gunay, W. O'Brien, I. Beausoleil-morrison, J. Bursill Development and implementation of a thermostat learning algorithm Sci. Technol. Built Environ., 4731 (December 2017) (2017), pp. 1-14

G.P. Henze, D.E. Kalz, S. Liu, C. Felsmann Experimental analysis of model-based predictive optimal control for active and passive building thermal storage inventory HVAC R Res., 11 (2) (2005), pp. 189-213

Z. Ma, P. Cooper, D. Daly, L. Ledo Existing building retrofits: methodology and state-of-the-art Energy Build., 55 (2012), pp. 889-902

P.-D. Moroşan, R. Bourdais, D. Dumur, J. Buisson Building temperature regulation using a distributed model predictive control Energy Build., 42 (9) (2010), pp. 1445-1452

H.B. Gunay, W. O'Brien, I. Beausoleil-Morrison, S. Gilani Development and implementation of an adaptive lighting and blinds control algorithm Build. Environ., 113 (2017), pp. 185-199

J. Woolley, M. Pritoni, M. Modera, W. Center Why occupancy-responsive adaptive thermostats do not always save-and the limits for when they should ACEEE Summer Study Energy Effic. Build. (2014), pp. 337-350

H.B. Gunay, J. Bursill, B. Huchuk, W. O'Brien, I. Beausoleil-Morrison Shortest-prediction-horizon model-based predictive control for individual offices Build. Environ., 82 (2014), pp. 408-419

M. Deru, P. Torcellini, N.R.E. Laboratory Performance Metrics Research Project - Final Report (2005)

D.T.J. O'Sullivan, M.M. Keane, D. Kelliher, R.J. Hitchcock Improving building operation by tracking performance metrics throughout the building lifecycle (BLC) Energy Build., 36 (11) (2004), pp. 1075-1090

C.F. Reinhart, J. Mardaljevic, Z. Rogers Dynamic daylight performance metrics for sustainable building design LEUKOS - J. Illum. Eng. Soc. North Am., 3 (1) (2006), pp. 7-31

W. O'Brien, I. Gaetani, S. Carlucci, P.-J. Hoes, J.L.M. Hensen On occupant-centric building performance metrics Build. Environ., 122 (2017), pp. 373-385

R. Hitchcock High-performance commercial building systems Program Stand. Build. Perform. Met. Final (2003), pp. 1-36

O.T. Masoso, L.J. Grobler The dark side of occupants' behaviour on building energy use Energy Build., 42 (2010), pp. 173-177

D. Harris, C. Higgins Methodology for Reporting Commercial Office Plug Load Energy Use (2013)

C.R. Bayliss, B.J. Hardy Transmission and Distribution Electrical Engineering (fourth ed.), Elsevier Ltd (2012)

J. Norman, H.L. Maclean, M. Asce, C.A. Kennedy “Comparing High and Low Residential Density : Life-Cycle Analysis of Energy Use and Greenhouse Gas Emissions, vol. 132 (2006), pp. 10-21

W. Kampel, S. Carlucci, B. Aas, A. Bruland A proposal of energy performance indicators for a reliable benchmark of swimming facilities Energy Build., 129 (2016), pp. 186-198

R.J. Hitchcock, M.A. Piette, S.E. Selkowitz Performance Metrics and Life-Cycle Information Management for Building Performance Assurance (1998)

K.M. Fowler, A.E. Solana, K.L. Spees Building Cost and Performance Metrics : Data Collection Protocol Revision 1 . 1 Pacific Northwest Natl. Lab. (2005)

N. Nassif A robust CO 2-based demand-controlled ventilation control strategy for multi-zone HVAC systems Energy Build., 45 (2012), pp. 72-81

W.J. Fisk, A.T. De Almeida Sensor-based demand-controlled ventilation: a review Energy Build., 29 (1) (1998), pp. 35-45

T. Hong, W.J. Fisk Assessment of Energy Savings Potential from the Use of Demand Controlled Ventilation in General Office Spaces in California (2010), pp. 117-124

I.E. Bennet, W. O'Brien Office building plug and light loads: comparison of a multi-tenant office tower to conventional assumptions Energy Build., 153 (2017), pp. 461-475

J. Page, D. Robinson, N. Morel, J. Scartezzini A generalised stochastic model for the simulation of occupant presence 40 (2008), pp. 83-98

D. Wang, C.C. Federspiel, F. Rubinstein Modeling occupancy in single person offices Energy Build., 37 (2) (2005), pp. 121-126

W. Shen, G. Newsham, B. Gunay Leveraging existing occupancy-related data for optimal control of commercial office buildings : a review Adv. Eng. Inf., 33 (2017), pp. 230-242

K. Christensen, R. Melfi, B. Nordman, B. Rosenblum, R. Viera Using existing network infrastructure to estimate building occupancy and control plugged-in devices in user workspaces Int. J. Commun. Netw. Distrib. Syst., 12 (1) (2014), pp. 4-29

H.B. Gunay, A.F. Fuller, W. O'Brien, I. Beausoleil-Morrison Detecting Occupants' Presence in Office Spaces: A Case Study eSim 2016 (2016)

D. Minoli, K. Sohraby, B. Occhiogrosso IoT considerations, requirements, and architectures for smart buildings – energy optimization and next generation building management systems IEEE Internet Things J., 4 (1) (2017), pp. 269-283
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