Improved long-term thermal comfort indices for continuous monitoring

• Published in: Energy and buildings 2020-10, Vol.224, p.110270, Article 110270
• Main Authors: Li, Peixian, Parkinson, Thomas, Schiavon, Stefano, Froese, Thomas M., de Dear, Richard, Rysanek, Adam, Staub-French, Sheryl
• Format: Article
• Language: English
• Subjects: Air conditioners; Building performance; Buildings; Continuous monitoring; Correlation analysis; Data driven methods; Monitoring; Occupancy; Office buildings; Post occupancy evaluation; Post occupancy evaluation (POE); Predicted Mean Vote index; Temperature; Thermal comfort; Workplace satisfaction
• ISSN: 0378-7788; 1872-6178
• DOI: 10.1016/j.enbuild.2020.110270

[Display omitted] •PMV/PPD based long-term indices do not correlate with the subjective evaluations.•The best existing index is %time that operative temperature falls outside a range.•Indices based on mean and overall variance of temperature have moderate performance.•The best new index is the frequency of daily temperature range exceeding 2 °C.•We recommend a new, combined index to evaluate long-term thermal comfort. Thermal comfort standards have suggested a number of physical indices which can be calculated from either building simulations or in situ physical monitoring to assess the long-term thermal comfort of a space. However, the prohibitively high cost of sensor technologies has limited the applications of these physical indices, and their usefulness has never been established using data collected in real buildings. This paper is the first assessment of the six types of existing indices (23 total) found in standards and five types of new indices (36 total) and their correlation with the long-term thermal satisfaction of building occupants. Correlation analyses were based on continuous thermal comfort measurements and post-occupancy evaluation surveys from four air-conditioned office buildings in Sydney, Australia. We found that the majority of existing indices, especially those based on predicted mean vote (PMV) and predicted percentage dissatisfied (PPD) metrics, have a weak correlation with thermal satisfaction. The percentage of time outside a temperature range was the best-performing index from the standards (r=-0.63). A new index based on the percentage of time that daily temperature range is greater than a threshold reported the strongest correlation (r=-0.8) with thermal satisfaction for this dataset. The results suggest that occupants’ long-term thermal comfort is influenced more by pronounced excursions beyond some acceptable temperature range and large variations in daily temperature than the average experience over time. These findings support the use of continuous monitoring technologies for long-term thermal comfort evaluation and inform potential amendments of international thermal comfort standards.