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06 September 2017
Lightweight and adaptive building simulation (LABS) framework for integrated building energy and thermal comfort analysis
Carol C. Menassa(
),
),
Keywords:
thermal comfort, energy simulation, distributed simulation, lightweight and adaptive building simulation, occupant behavior model
Cite this article:
Thomas A, Menassa CC, Kamat VR.
Lightweight and adaptive building simulation (LABS) framework for integrated building energy and thermal comfort analysis.
Building Simulation,
2017, 10(6): 1023-1044.
https://doi.org/10.1007/s12273-017-0409-5
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Coupled and distributed simulation helps in understanding the complexity arising from the combined effects of interdependent systems, by connecting and exchanging information across several software programs. In the building energy analysis domain, several tools have been created in the past to facilitate such analyses. However, the existing coupling frameworks such as Building Control Virtual Test Bed (BCVTB), MLE+, High-Level Architecture (HLA), and Functional Mockup Unit are characterized by their inherent complexity, making it a challenge for the building practitioners to widely deploy them in everyday decision-making. In addition, several of these frameworks embody tight coupling, which means they lack the flexibility to incorporate models and components of decision-makers’ choice. This study addresses these gaps by proposing a Lightweight and Adaptive Building Simulation (LABS) framework that capitalizes on Lightweight Communications and Marshalling (LCM), an inter-process communication framework widely used by the robotics community. As a case study demonstrating this new framework, a building energy simulation model is coupled with an agent-based occupant behavior model to understand the energy effects of occupants’ thermal comfort related actions (e.g., adjusting the thermostat set point). These behavioral patterns are also influenced by various interventions (e.g., peer pressure, energy-based education) that may occur in the building. Measuring these effects in a real building for a lengthy period is impractical and resource-intensive and the LABS framework can be used for understanding this system better. The results also highlight opportunities for achieving energy savings by influencing the occupants’ comfort related behavior.
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Lightweight and adaptive building simulation (LABS) framework for integrated building energy and thermal comfort analysis
Carol C. Menassa(
),
),
Abstract
Coupled and distributed simulation helps in understanding the complexity arising from the combined effects of interdependent systems, by connecting and exchanging information across several software programs. In the building energy analysis domain, several tools have been created in the past to facilitate such analyses. However, the existing coupling frameworks such as Building Control Virtual Test Bed (BCVTB), MLE+, High-Level Architecture (HLA), and Functional Mockup Unit are characterized by their inherent complexity, making it a challenge for the building practitioners to widely deploy them in everyday decision-making. In addition, several of these frameworks embody tight coupling, which means they lack the flexibility to incorporate models and components of decision-makers’ choice. This study addresses these gaps by proposing a Lightweight and Adaptive Building Simulation (LABS) framework that capitalizes on Lightweight Communications and Marshalling (LCM), an inter-process communication framework widely used by the robotics community. As a case study demonstrating this new framework, a building energy simulation model is coupled with an agent-based occupant behavior model to understand the energy effects of occupants’ thermal comfort related actions (e.g., adjusting the thermostat set point). These behavioral patterns are also influenced by various interventions (e.g., peer pressure, energy-based education) that may occur in the building. Measuring these effects in a real building for a lengthy period is impractical and resource-intensive and the LABS framework can be used for understanding this system better. The results also highlight opportunities for achieving energy savings by influencing the occupants’ comfort related behavior.
Keywords:
thermal comfort, energy simulation, distributed simulation, lightweight and adaptive building simulation, occupant behavior model
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Publication history
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Acknowledgements
Publication history
Received: 15 December 2016
Revised: 03 July 2017
Accepted: 07 August 2017
Published:
06 September 2017
Issue date: December 2017
Copyright
© Tsinghua University Press and Springer-Verlag GmbH Germany 2017
Acknowledgements
The authors would like to acknowledge the financial support received for this research from the U.S. National Science Foundation (NSF) through grants NSF-1349921, NSF-1407908 and NSF-1638186. Any opinions and findings in this paper are those of the authors and do not necessarily represent those of the NSF.
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