Maintaining Thermal Comfort of a Naturally Ventilated Residential House by Intelligently Actuating Windows

Pokhrel, M
Anderson, T
Lie, T
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Conference Contribution
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The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong

In New Zealand’s (NZ) mild climatic conditions, most residential houses are ventilated naturally, mainly by opening windows. However, maintaining the indoor thermal comfort characteristics of a house by modulating natural ventilation is particularly challenging, as the solution is not explicit. Determining a solution requires a technique that adjusts openable window area while encapsulating the complexity, dynamics, and nonlinearity associated with the natural ventilation driving forces and building thermal behavior. By verifying that there exists a significant potential of regulating indoor thermal comfort of a relatively airtight and insulated house by adjusting window openable area; this work additionally confirmed an excellent capability of Artificial Neural Network (ANN) technique in predicting air temperature time-series of the naturally ventilated house. On the basis of these examinations, this work particularly developed a co-simulation strategy between building thermal-airflow model and the ANN model and demonstrated that windows could be regulated intelligently to modulate the natural ventilation and maintain indoor thermal comfort level during the summer period by applying Artificial Neural Network (ANN) based predictive controller technique.

Natural Ventilation , Thermal Comfort , Artificial Neural Network (ANN) , Residential House , Intelligent Windows
Intelligent & Informed, Proceedings of the 24th International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA) 2019, Volume 1, 705-714. © 2019 and published by the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong.
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