An agent-based framework to study occupant multi-comfort level in office buildings

Barakat, Mohammad; Khoury, Hiam

doi:10.1109/wsc.2016.7822187

Cited by 6 publications

(4 citation statements)

References 21 publications

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“…Different research studies have adopted ABM for various objectives. For example, Barakat and Khoury (2016) used ABM to study occupant multi-comfort level to reduce energy consumption within academic buildings. Haryadi et al (2019) predicted future rooftop photovoltaic adoption through ABM to understand the impact of the decisionmaking behavior on electricity utilization.…”

Section: Methodsmentioning

confidence: 99%

Pull planning versus push planning: Investigating impacts on crew performance from a location-based perspective

Ghanem

Hamzeh

Seppänen

et al. 2022

Front. Built Environ.

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Push planning and pull planning are different approaches used for production planning and control. Push planning uses predetermined dates to control a project, whereas pull planning utilizes the system’s current state. Although researchers have compared these approaches from production planning perspective to improve project performance, the differences between push and pull in construction and their impacts on crew performance and congestion have not yet been explored. Therefore, this research aims to investigate the underlying mechanisms of applying pull and push approaches at the location level through simulation, in addition to proposing hypotheses relating push and pull approaches to project and crew performance metrics. Agent-based modeling is used to simulate and describe how push and pull approaches affect crew performance. Results show that pull approaches can achieve significantly higher productivity, less idle time, lower crew turnover, and fewer task interruptions, although they can result in slightly increased project durations. Cross-analyzing the mentioned results with other performance metrics reveals that push and pull approaches should be applied together to achieve a flexible production control system. The significance of this study is embedded in exploring and understanding how the choice of push and pull planning approaches impacts the location-based management of tasks and crew performance. Such impacts on productivity, crew performance, and the flow of site operations enable a convergence to generalized conclusions regarding the efficacy of each method.

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Section: Methodsmentioning

confidence: 99%

Pull planning versus push planning: Investigating impacts on crew performance from a location-based perspective

Ghanem

Hamzeh

Seppänen

et al. 2022

Front. Built Environ.

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“…Occupants interact with building systems to respond to change through adaptation and learning [57,58]. The MAS provides an opportunity to further understand the impact of occupant behavior on energy consumption.…”

Section: Multi-agent-based Modelingmentioning

confidence: 99%

Occupant Behavior Impact on Building Sustainability Performance: A Literature Review

Ebuy

Haouzi

Benelmir³

et al. 2023

Sustainability

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Occupant behavior controls a building’s energy system to adapt the indoor environment, significantly increasing building energy consumption. Occupant behavior, which refers to the occupancy inside a building and their interaction with building systems (windows, blinds, thermostats, lighting and appliances, etc.), has been largely overlooked in building energy performance analysis. These factors make it essential to design sustainable buildings. It is widely acknowledged in the literature that there is an alarming performance gap between the estimated and actual energy consumption in buildings. This paper proposes a systematic literature review on energy-related occupant behaviors and their implications for energy performance. It aims to better understand occupant behavior, existing behavior modeling approaches and their limitations, and key influential parameters on building energy performance. It is based on a survey of ScienceDirect, Web of science and Scopus scientific databases, using their bibliometric analysis tools together with the VOSviewer software. Finally, this study identifies the following significant research gaps for future development: limitations of the generic and robust occupant behavior model; lack of actual data for validation; lack of research on different types of buildings (institutions, university buildings); limitations of considering all factors which influence occupant behavior; missing the detailed realistic situations of occupant behavior; integrating building information modeling (BIM) into building energy modeling.

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“…Furthermore, Virote and Neves-Silva [11] explored the applicability of stochastic models to represent the space occupancy and the occupant's behavior. On the other hand, ABM has been widely used to simulate the interaction of occupants with their environment and with other agents [12][13][14][15] and has proven very promising in reflecting occupant's sensation, perception, inference, and interaction. For instance, Lee and Malkawi [13] used ABM to allow agents to adapt to their environment by making reasonable behavioral decisions based on their comfort.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Lee and Malkawi [13] used ABM to allow agents to adapt to their environment by making reasonable behavioral decisions based on their comfort. Similarly, Barakat and Khoury [14] employed an agent-based framework to study occupant multi-comfort level for building energy optimization.…”

Section: Introductionmentioning

confidence: 99%

Behavioral and parametric effects on energy consumption through BIM, BEM, and ABM

Hajj-Hassan¹,

Khoury²

2018

Creative Construction Conference 2018 - Proceedings

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Over the past years, several tools and methods have been developed to address performance-related designs and provide designers with integrative platforms to estimate building energy consumption and mitigate its impact. However, the predictions obtained through different energy modeling engines have been typically deviating from the actual energy consumption. As such, many efforts have attempted at bridging this so-called "performance gap. Nonetheless, this was conducted in a fragmented fashion whereby synchronizing the geometric exchange of Building Information Modeling (BIM) to Building Energy Modeling (BEM) was done independently from incorporating, through Agent-Based Modelling (ABM), building occupants' behavior vis-à-vis energy consumption. Therefore, this paper merges the aforementioned approaches and presents work targeted at assessing the diverse and dynamic energy-use behavior of occupants using BIM, BEM and ABM. To that end, a simulation environment was developed to study both the parametric design and behavioural factors. The design parameters included within a BIM model were utilized to set the thermal zone, the internal zone gains were defined using ABM, and resulting data was exported as an input data file to EnergyPlus. Several experiments have been conducted for the case of an academic office and results of the energy analysis highlighted a variation of up to 11% as compared to static occupant behavioral patterns generally adopted.

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An agent-based framework to study occupant multi-comfort level in office buildings

Cited by 6 publications

References 21 publications

Pull planning versus push planning: Investigating impacts on crew performance from a location-based perspective

Pull planning versus push planning: Investigating impacts on crew performance from a location-based perspective

Occupant Behavior Impact on Building Sustainability Performance: A Literature Review

Behavioral and parametric effects on energy consumption through BIM, BEM, and ABM

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