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Residential ventilation system optimization using Monte-Carlo and genetic algorithm techniques

Jelle Laverge (UGent) and Arnold Janssens (UGent)
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Abstract
This paper demonstrates the use of Monte-Carlo and Genetic Algorithm techniques combined with multizone simulations for the optimization of residential ventilation systems in order to reduce exposure to airborne contaminants. In the paper, both the optimization of constant flow rate systems and of demand controlled systems is discussed and their performance related to exposure and energy loss are assessed. First, a number of realistic parameters are defined that characterise possible system configurations. The simulations are used to assess the performance of these configurations. The results show that mechanical ventilation systems offer lower exposure for a given heat loss compared to natural ventilation systems. Furthermore, demand controlled systems prove to provide even lower exposure for the same heat loss. The paper clearly demonstrates the differences between different system layouts in optimal configurations.
Keywords
optimization, Monte Carlo, residential ventilation, genetic algorithm

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Chicago
Laverge, Jelle, and Arnold Janssens. 2010. “Residential Ventilation System Optimization Using Monte-Carlo and Genetic Algorithm Techniques.” In ASHRAE IAQ, 16th Conference, Proceedings. American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE).
APA
Laverge, J., & Janssens, A. (2010). Residential ventilation system optimization using Monte-Carlo and genetic algorithm techniques. ASHRAE IAQ, 16th Conference, Proceedings. Presented at the 16th ASHRAE IAQ conference (IAQ 2010) : Airborne infection control : ventilation, IAQ and energy, American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE).
Vancouver
1.
Laverge J, Janssens A. Residential ventilation system optimization using Monte-Carlo and genetic algorithm techniques. ASHRAE IAQ, 16th Conference, Proceedings. American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE); 2010.
MLA
Laverge, Jelle, and Arnold Janssens. “Residential Ventilation System Optimization Using Monte-Carlo and Genetic Algorithm Techniques.” ASHRAE IAQ, 16th Conference, Proceedings. American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), 2010. Print.
@inproceedings{1150359,
  abstract     = {This paper demonstrates the use of Monte-Carlo and Genetic Algorithm techniques combined with multizone simulations for the optimization of residential ventilation systems in order to reduce exposure to airborne contaminants. In the paper, both the optimization of constant flow rate systems and of demand controlled systems is discussed and their performance related to exposure and energy loss are assessed.
First, a number of realistic parameters are defined that characterise possible system configurations. The simulations are used to assess the performance of these configurations. The results show that mechanical ventilation systems offer lower exposure for a given heat loss compared to natural ventilation systems. Furthermore, demand controlled systems prove to provide even lower exposure for the same heat loss. The paper clearly demonstrates the differences between different system layouts in optimal configurations.},
  articleno    = {C149},
  author       = {Laverge, Jelle and Janssens, Arnold},
  booktitle    = {ASHRAE IAQ, 16th Conference, Proceedings},
  isbn         = {9781936504046},
  keyword      = {optimization,Monte Carlo,residential ventilation,genetic algorithm},
  language     = {eng},
  location     = {Kuala Lumpur, Malyasia},
  pages        = {10},
  publisher    = {American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE)},
  title        = {Residential ventilation system optimization using Monte-Carlo and genetic algorithm techniques},
  year         = {2010},
}