<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Buildings are interactive environments in which their operations and occupants are linked. Although buildings are operated according to the standards, occupant complaints may arise when there is a mismatch between indoor environmental conditions and actual user needs. Therefore, the accuracy of thermal comfort prediction models suggested by the standards and alternative prediction models need to be investigated. This study aims at assessing the performance of the predicted mean vote (PMV) model suggested by the ISO 7730 Standard to detect occupant thermal dissatisfaction. In addition, a multivariate logistic regression model was developed to predict thermal complaints with respect to “too warm” and “too cold.” This case study was conducted in a commercial building located in Paris, France, between January 2017 and May 2018. Indoor environmental conditions were monitored via sensors and an online tool was used to collect occupant thermal complaints. A total of 53 thermal complaints were analyzed. The results showed that all the operative temperature measurements in both the heating and cooling seasons were within the thresholds suggested by the standards. The PMV method suggested that only 4% of the occupants were dissatisfied with the indoor environment whereas the actual dissatisfaction ratio was 100% under these indoor environmental conditions. In addition, the multivariate logistic regression model showed that operative temperature and season have a significant effect on thermal complaints. Furthermore, the accuracy of the developed model was 90.6%.</p>
</abstract>

Buildings are interactive environments in which their operations and occupants are linked. Although buildings are operated according to the standards, occupant complaints may arise when there is a mismatch between indoor environmental conditions and actual user needs. Therefore, the accuracy of thermal comfort prediction models suggested by the standards and alternative prediction models need to be investigated. This study aims at assessing the performance of the predicted mean vote (PMV) model suggested by the ISO 7730 Standard to detect occupant thermal dissatisfaction. In addition, a multivariate logistic regression model was developed to predict thermal complaints with respect to “too warm” and “too cold.” This case study was conducted in a commercial building located in Paris, France, between January 2017 and May 2018. Indoor environmental conditions were monitored via sensors and an online tool was used to collect occupant thermal complaints. A total of 53 thermal complaints were analyzed. The results showed that all the operative temperature measurements in both the heating and cooling seasons were within the thresholds suggested by the standards. The PMV method suggested that only 4% of the occupants were dissatisfied with the indoor environment whereas the actual dissatisfaction ratio was 100% under these indoor environmental conditions. In addition, the multivariate logistic regression model showed that operative temperature and season have a significant effect on thermal complaints. Furthermore, the accuracy of the developed model was 90.6%.

Analyzing and modeling thermal complaints in a commercial building in France

Organization, Technology and Management in Construction: an International Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Analyzing and modeling thermal complaints in a commercial building in France"}

Buildings are interactive environments in which their operations and occupants are linked. Although buildings are operated according to the standards, occupant...

Analyzing and modeling thermal complaints in a commercial building in France

Article Category: Research Paper

Pubblicato online: 31 lug 2021

Pagine: 2416 - 2425

Ricevuto: 06 gen 2020

Accettato: 22 mar 2020

DOI: https://doi.org/10.2478/otmcj-2020-0017

Parole chiave
thermal dissatisfaction, thermal complaint, PMV–PPD model, logistic regression

© 2021 Ezgi Kocaman et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Analyzing and modeling thermal complaints in a commercial building in France

Article Category: Research Paper

Pubblicato online: 31 lug 2021

Pagine: 2416 - 2425

Ricevuto: 06 gen 2020

Accettato: 22 mar 2020

DOI: https://doi.org/10.2478/otmcj-2020-0017

Parole chiavethermal dissatisfaction, thermal complaint, PMV–PPD model, logistic regression

© 2021 Ezgi Kocaman et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
thermal dissatisfaction, thermal complaint, PMV–PPD model, logistic regression