CO2-based grey-box model to estimate airflow rate and room occupancy

Sebastian Wolf, Maria Justo Alonso, Davide Cali, John Krogstie, Hans Martin Mathisen, Henrik Madsen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

In the existing building stock, heating, cooling and ventilation often run on fixed schedules assuming maximal occupancy. However, fitting the control of the HVAC system to the building's real demand offers large potential for energy savings over the status quo. Building occupants' presence as well as mechanically supplied and infiltrated airflow rates provide information that enables to define tailored strategies for demand-controlled ventilation. Hence, real-time estimations of these quantities are a valuable input to demand-controlled built environments. In this work, the use of stochastic differential equations (SDE) to estimate the room occupancy, infiltration air-rate and ventilation air-rate is investigated. In particular, a grey-box model based on a carbon dioxide (CO2) mass balance equation is presented. The model combines knowledge about the physical system with statistical, data-driven parameter estimation. Furthermore, the proposed model contains uncertainty parameters. This is in contrast to purely deterministic models based on ordinary differential equations, where uncertainty is usually disregarded. The suggested model has been tested in a naturally ventilated and in a mechanically ventilated environment; the performance in these two cases has been compared. We show that the ability to address measurement errors and non-homogeneous conditions in the room air implies that the suggested SDE-based grey-box approach is suitable in the context of demand-controlled ventilation.
Original languageEnglish
Title of host publicationProceedings of 13th REHVA World Congress
Number of pages7
PublisherEDP Sciences
Publication date2019
Article number04036
DOIs
Publication statusPublished - 2019
EventClima 2019: 13th REHVA World Congress - Bucharest, Romania
Duration: 26 May 201929 May 2019
Conference number: 13

Conference

ConferenceClima 2019: 13th REHVA World Congress
Number13
CountryRomania
CityBucharest
Period26/05/201929/05/2019
SeriesE3S Web of Conferences
Volume111
ISSN2267-1242

Cite this

Wolf, S., Alonso, M. J., Cali, D., Krogstie, J., Mathisen, H. M., & Madsen, H. (2019). CO2-based grey-box model to estimate airflow rate and room occupancy. In Proceedings of 13th REHVA World Congress [04036] EDP Sciences. E3S Web of Conferences, Vol.. 111 https://doi.org/10.1051/e3sconf/201911104036
Wolf, Sebastian ; Alonso, Maria Justo ; Cali, Davide ; Krogstie, John ; Mathisen, Hans Martin ; Madsen, Henrik. / CO2-based grey-box model to estimate airflow rate and room occupancy. Proceedings of 13th REHVA World Congress. EDP Sciences, 2019. (E3S Web of Conferences, Vol. 111).
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Wolf, S, Alonso, MJ, Cali, D, Krogstie, J, Mathisen, HM & Madsen, H 2019, CO2-based grey-box model to estimate airflow rate and room occupancy. in Proceedings of 13th REHVA World Congress., 04036, EDP Sciences, E3S Web of Conferences, vol. 111, Clima 2019: 13th REHVA World Congress, Bucharest, Romania, 26/05/2019. https://doi.org/10.1051/e3sconf/201911104036

CO2-based grey-box model to estimate airflow rate and room occupancy. / Wolf, Sebastian; Alonso, Maria Justo; Cali, Davide; Krogstie, John; Mathisen, Hans Martin; Madsen, Henrik.

Proceedings of 13th REHVA World Congress. EDP Sciences, 2019. 04036 (E3S Web of Conferences, Vol. 111).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Wolf S, Alonso MJ, Cali D, Krogstie J, Mathisen HM, Madsen H. CO2-based grey-box model to estimate airflow rate and room occupancy. In Proceedings of 13th REHVA World Congress. EDP Sciences. 2019. 04036. (E3S Web of Conferences, Vol. 111). https://doi.org/10.1051/e3sconf/201911104036