Validation, optimisation and comparison of carbon dioxide-based occupancy estimation algorithms. Issue 6 (July 2020)

• Record Type: Journal Article
• Authors: Nienaber, Felix; Wolf, Sebastian; Wesseling, Mark; Calì, Davide; Müller, Dirk; Madsen, Henrik
• Other Names: Kosonen Risto guest-editor.
• Is Part Of: Indoor + built environment. Volume 29:Issue 6(2020)
• Page Start: 820
• Page End: 834
• Publication Date: 2020-07
• Subjects: CO2 -- Occupancy detection -- Indoor air quality -- Occupant behaviour; Indoor air pollution -- Periodicals; Sick building syndrome -- Periodicals; Buildings -- Environmental engineering -- Periodicals; Environmental health -- Periodicals; 613.5
• DOI: 10.1177/1420326X19871332
• Languages: English
• ISSNs: 1420-326X

Abstract

The operation of heating, cooling and air-conditioning (HVAC) in buildings often adheres to fixed time schedules. However, associating HVAC schedules to the occupant's presence patterns can save a significant amount of energy, reducing operation periods to the required minimum. Therefore, automated occupancy estimation provides valuable input to efficient building control strategies. This work discusses the validation and adjustment for two carbon dioxide-based occupancy detection algorithms based on data from ten multi-person offices. Both methods are based on a carbon dioxide mass balance equation. However, they follow two different philosophies. One model is deterministic and includes a more detailed representation of the system, whereas the other model includes stochastic elements and was based on fewer assumptions. Both approaches show similar and promising results. The advantages and drawbacks of each method are reviewed. Furthermore, adjustments of the algorithms to the given conditions and possible future improvements are discussed.