Development of Synthetic Ageing Profiling for Occupant Behaviour

Yuezhong Liu; Yin Leng Theng

doi:10.26868/25222708.2021.30383

Development of Synthetic Ageing Profiling for Occupant Behaviour

Yuezhong Liu, Yin Leng Theng

Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Occupant behaviour is one major factor influencing energy use in residential buildings, which is also impacted by sociodemographic such as age. A better understanding of age-behaviour-building interactions enables to describe with higher accuracy the energy consumption as the ageing population increase rapidly. However, the collection of real occupant behaviour faces difficulties in privacy issues and various sensors with relatively high costs. This pilot study proposed to develop synthetic ageing profiling for occupant behaviour through the Generative Adversarial Network (GAN), which is capable of predicting electricity consumption by simulation tool (EnergyPlus) during the design process. We validated the results with 600 household profiles with two-generational cohorts (40-64 years and 65 years and above) in Singapore. The Kullback-Leibler divergence of the synthetic and real profiling are within 0.46 for a majority of parameters and clusters. The synthetic results will help the building energy performance research for an ageing population.

Original language	English
Title of host publication	BS 2021 - Proceedings of Building Simulation 2021
Subtitle of host publication	17th Conference of IBPSA
Editors	Dirk Saelens, Jelle Laverge, Wim Boydens, Lieve Helsen
Publisher	International Building Performance Simulation Association
Pages	3498-3504
Number of pages	7
ISBN (Electronic)	9781775052029
DOIs	https://doi.org/10.26868/25222708.2021.30383
Publication status	Published - 2022
Externally published	Yes
Event	17th IBPSA Conference on Building Simulation, BS 2021 - Bruges, Belgium Duration: Sept 1 2021 → Sept 3 2021

Publication series

Name	Building Simulation Conference Proceedings
ISSN (Print)	2522-2708

Conference

Conference	17th IBPSA Conference on Building Simulation, BS 2021
Country/Territory	Belgium
City	Bruges
Period	9/1/21 → 9/3/21

Bibliographical note

Publisher Copyright:
© International Building Performance Simulation Association, 2022

ASJC Scopus Subject Areas

Building and Construction
Architecture
Modelling and Simulation
Computer Science Applications

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.26868/25222708.2021.30383

Cite this

Liu, Y., & Theng, Y. L. (2022). Development of Synthetic Ageing Profiling for Occupant Behaviour. In D. Saelens, J. Laverge, W. Boydens, & L. Helsen (Eds.), BS 2021 - Proceedings of Building Simulation 2021: 17th Conference of IBPSA (pp. 3498-3504). (Building Simulation Conference Proceedings). International Building Performance Simulation Association. https://doi.org/10.26868/25222708.2021.30383

Liu, Yuezhong ; Theng, Yin Leng. / Development of Synthetic Ageing Profiling for Occupant Behaviour. BS 2021 - Proceedings of Building Simulation 2021: 17th Conference of IBPSA. editor / Dirk Saelens ; Jelle Laverge ; Wim Boydens ; Lieve Helsen. International Building Performance Simulation Association, 2022. pp. 3498-3504 (Building Simulation Conference Proceedings).

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abstract = "Occupant behaviour is one major factor influencing energy use in residential buildings, which is also impacted by sociodemographic such as age. A better understanding of age-behaviour-building interactions enables to describe with higher accuracy the energy consumption as the ageing population increase rapidly. However, the collection of real occupant behaviour faces difficulties in privacy issues and various sensors with relatively high costs. This pilot study proposed to develop synthetic ageing profiling for occupant behaviour through the Generative Adversarial Network (GAN), which is capable of predicting electricity consumption by simulation tool (EnergyPlus) during the design process. We validated the results with 600 household profiles with two-generational cohorts (40-64 years and 65 years and above) in Singapore. The Kullback-Leibler divergence of the synthetic and real profiling are within 0.46 for a majority of parameters and clusters. The synthetic results will help the building energy performance research for an ageing population.",

author = "Yuezhong Liu and Theng, {Yin Leng}",

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doi = "10.26868/25222708.2021.30383",

language = "English",

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Liu, Y & Theng, YL 2022, Development of Synthetic Ageing Profiling for Occupant Behaviour. in D Saelens, J Laverge, W Boydens & L Helsen (eds), BS 2021 - Proceedings of Building Simulation 2021: 17th Conference of IBPSA. Building Simulation Conference Proceedings, International Building Performance Simulation Association, pp. 3498-3504, 17th IBPSA Conference on Building Simulation, BS 2021, Bruges, Belgium, 9/1/21. https://doi.org/10.26868/25222708.2021.30383

Development of Synthetic Ageing Profiling for Occupant Behaviour. / Liu, Yuezhong; Theng, Yin Leng.
BS 2021 - Proceedings of Building Simulation 2021: 17th Conference of IBPSA. ed. / Dirk Saelens; Jelle Laverge; Wim Boydens; Lieve Helsen. International Building Performance Simulation Association, 2022. p. 3498-3504 (Building Simulation Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Y1 - 2022

N2 - Occupant behaviour is one major factor influencing energy use in residential buildings, which is also impacted by sociodemographic such as age. A better understanding of age-behaviour-building interactions enables to describe with higher accuracy the energy consumption as the ageing population increase rapidly. However, the collection of real occupant behaviour faces difficulties in privacy issues and various sensors with relatively high costs. This pilot study proposed to develop synthetic ageing profiling for occupant behaviour through the Generative Adversarial Network (GAN), which is capable of predicting electricity consumption by simulation tool (EnergyPlus) during the design process. We validated the results with 600 household profiles with two-generational cohorts (40-64 years and 65 years and above) in Singapore. The Kullback-Leibler divergence of the synthetic and real profiling are within 0.46 for a majority of parameters and clusters. The synthetic results will help the building energy performance research for an ageing population.

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Liu Y, Theng YL. Development of Synthetic Ageing Profiling for Occupant Behaviour. In Saelens D, Laverge J, Boydens W, Helsen L, editors, BS 2021 - Proceedings of Building Simulation 2021: 17th Conference of IBPSA. International Building Performance Simulation Association. 2022. p. 3498-3504. (Building Simulation Conference Proceedings). doi: 10.26868/25222708.2021.30383

Development of Synthetic Ageing Profiling for Occupant Behaviour

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus Subject Areas

UN SDGs

Access to Document

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Cite this