Quantifying the impact of occupants’ spatial distributions on office buildings energy and comfort performance

Abuimara, Tareq; O’Brien, William; Gunay, H. Burak

doi:10.1016/j.enbuild.2020.110695

Cited by 17 publications

(7 citation statements)

References 43 publications

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“…Occupancy-based VAV control enhances energy savings by regulating the distribution of ventilation across a building's zones in a way that assists in eliminating the discomfort and inefficiencies that result from the over-ventilation of under-occupied zones, and under-ventilation of over-occupied zones. 76,77 Lighting can be adapted to occupant presence using motion detectors at various levels of granularity, with high energy savings generally possible as the sensor grid density increases. 57 Online learning algorithms can be deployed in controllers to passively inferring occupants' preferred illuminance setpoints in real time (e.g., Gunay et al 22 ); occupants' preferences can also be learned actively by explicitly asking occupants using enabling technologies such as mobile applications or wearables (e.g., Jayathissa et al, 78 Sood et al, 79 Konis et al 80 ).…”

Section: Occupant-centric Controlsmentioning

confidence: 99%

A data-driven workflow to improve energy efficient operation of commercial buildings: A review with real-world examples

Abuimara

Hobson

Gunay

et al. 2022

Building Services Engineering Research and Technology

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Data-driven building operation and maintenance research such as metadata inference, fault detection and diagnosis, occupant-centric controls (OCCs), and non-invasive load monitoring have emerged (NILM) as independent domains of study. However, there are strong dependencies between these domains; for example, quality of metadata affects the usability of fault detection and diagnostics techniques. Further, faults in controls hardware and programs limit the performance of OCCs. To this end, a literature review was conducted to identify the dependencies between these domains of research. Additionally, real-world examples using operational data from three institutional buildings in Ottawa, Canada, were provided and discussed to demonstrate these dependencies. Finally, a holistic tool-agnostic workflow was introduced which suggested the implementation of operational energy efficiency measures in the following order to ensure their full potential: (1) improve metadata, (2) address faults, (3) implement OCCs, and (4) monitor enhanced key performance indicators (KPIs). The proposed workflow is intended to be comprehensive, reproducible, nonintrusive, and inexpensive to implement. Practical applications: Optimization of building operations has been emerging among energy management professionals as a relatively low-cost means to achieve energy efficiency and minimize occupants’ discomfort. To this end, this study introduces a tool-agnostic data-driven workflow to building energy management practitioners that can assist them in achieving increased energy efficiency. The proposed workflow recognizes the interdependency of the various domains of research which have historically been treated independently.

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Section: Occupant-centric Controlsmentioning

confidence: 99%

A data-driven workflow to improve energy efficient operation of commercial buildings: A review with real-world examples

Abuimara

Hobson

Gunay

et al. 2022

Building Services Engineering Research and Technology

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“…The approaches based on thermal simulations still use simplified schedule occupancy to be able to predict the energy demand more closely to real cases [4]. Abuimara et al [21] and in a standard commercial building with a floor area of 1728 m², tested 75 occupants' distribution scenarios with an average density of 0.05 person/m², which remained unchanged for the entire building. A variation in occupancy density varied from 0 to 0.21 person/m².…”

Section: The Occupant Behaviormentioning

confidence: 99%

“…Building energy systems consider the quality and the technology of the HVAC systems. Dascalaki et al [10] introduced this register within a statistical approach and Abuimara et al [21] suggested improving the adaptability of the HVAC technology according to the buildings' occupancy. The number of variables selected varies relatively from one study to another, 17 for Amiri et al [2], 6 for Ali-Toudert and Weidhaus [26] and 7 for Bouyer [3], and 3 for Catalina et al [8].…”

Section: Building Energy Systemsmentioning

confidence: 99%

Predicting energy demand of residential buildings: A linear regression-based approach for a small sample size

Boukarta

2021

Selected Scientific Papers - Journal of Civil Engineering

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The key design strategies that reduce the energy demand of buildings are not present in most thermal codes in many countries. Therefore, modeling techniques offer an alternative to combine the architects' modus operandi with the energy efficiency in the early stages of architectural design and with higher speed and precision. However, a review of the scientific literature using modeling techniques shows that most researchers use a relatively large sample of thermal simulations. This paper proposes a simplified method based on the linear regression modeling technique and considers a relatively smaller sample of thermal simulations. A total of 6 key building design strategies were identified, related to the urban context, building envelope, and shape factor. A simulation protocol containing 60 possible combinations was designed by random selection. In the present study, the Pleiades software was used to estimate the annual energy demand for heating and cooling for a typical dwelling in a humid climate zone. A parametric study and sensitivity analysis to identify the most efficient parameters was performed in SPSS 21. The resulting model predicts the annual energy demand with an accuracy of 93.7%, a root mean square error (RMSE) of 5.88, and a scatter index (SI) of 8.59%. The models performed could efficiently and quickly assist architects while designing the buildings in the architectural practice.

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“…Energy use reduction, minimal material/resource use, and maximum effort towards recyclability are crucial for ensuring sustainable design (Bogdanov et al, 2021;Fernando et al, 2021;Mankoff et al, 2007;Thormark, 2007). Significant research efforts have been made to reduce the operational energy of buildings (Gao et al, 2020;Shoubi et al, 2015); researchers have identified factors which affect operational energy, such as building location, size, conservation policy, occupant behaviour, and room occupancy distribution patterns (Abuimara et al, 2021;Akande, 2015;Macknick et al, 2012;Rickwood, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…, 2020; Shoubi et al. , 2015); researchers have identified factors which affect operational energy, such as building location, size, conservation policy, occupant behaviour, and room occupancy distribution patterns (Abuimara et al. , 2021; Akande, 2015; Macknick et al.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the impact of material service life on embodied energy of residential villas in the United Arab Emirates

Rauf,

Attoye,

Crawford

2024

ECAM

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PurposeRecently, there has been a shift toward the embodied energy assessment of buildings. However, the impact of material service life on the life-cycle embodied energy has received little attention. We aimed to address this knowledge gap, particularly in the context of the UAE and investigated the embodied energy associated with the use of concrete and other materials commonly used in residential buildings in the hot desert climate of the UAE.Design/methodology/approachUsing input–output based hybrid analysis, we quantified the life-cycle embodied energy of a villa in the UAE with over 50 years of building life using the average, minimum, and maximum material service life values. Mathematical calculations were performed using MS Excel, and a detailed bill of quantities with >170 building materials and components of the villa were used for investigation.FindingsFor the base case, the initial embodied energy was 57% (7390.5 GJ), whereas the recurrent embodied energy was 43% (5,690 GJ) of the life-cycle embodied energy based on average material service life values. The proportion of the recurrent embodied energy with minimum material service life values was increased to 68% of the life-cycle embodied energy, while it dropped to 15% with maximum material service life values.Originality/valueThe findings provide new data to guide building construction in the UAE and show that recurrent embodied energy contributes significantly to life-cycle energy demand. Further, the study of material service life variations provides deeper insights into future building material specifications and management considerations for building maintenance.

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Quantifying the impact of occupants’ spatial distributions on office buildings energy and comfort performance

Cited by 17 publications

References 43 publications

A data-driven workflow to improve energy efficient operation of commercial buildings: A review with real-world examples

A data-driven workflow to improve energy efficient operation of commercial buildings: A review with real-world examples

Predicting energy demand of residential buildings: A linear regression-based approach for a small sample size

Evaluating the impact of material service life on embodied energy of residential villas in the United Arab Emirates

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