IIR document
On-site room air conditioners replacement test with limited data during COVID-19 regulation periods.
Number: 0305
Author(s) : WAN H., HWANG Y., ANDERSEN S. O.
Summary
A study was conducted in a bank branch in Marrakech, Morocco to explore substituting split Room Air Conditioners (RACs) with high-efficiency, low Global Warming Potential (GWP) refrigerant at an affordable cost. Due to COVID regulations, some weather data from 2020 was unavailable. A Shallow Neural Network was used to recover some of the lost on-site weather data from historical field tests and an open-source weather database, allowing us to make use of the incomplete data. In conclusion, using the predicted weather data, it was found that the new R-32 RACs installed in 2020 used 8 to 29% of the power consumed by the old R-22 RACs under the same ambient conditions in 2019. This was due to a higher indoor room temperature setting as the cold air was directed to occupants by an occupant sensor and a lower usage ratio by COVID regulation. Future work should update these findings with new measurements once the bank's operations return to normal following the easing of COVID regulations.
Available documents
Format PDF
Pages: 10
Available
Public price
20 €
Member price*
Free
* Best rate depending on membership category (see the detailed benefits of individual and corporate memberships).
Details
- Original title: On-site room air conditioners replacement test with limited data during COVID-19 regulation periods.
- Record ID : 30031505
- Languages: English
- Subject: Technology, Developing country
- Source: Proceedings of the 26th IIR International Congress of Refrigeration: Paris , France, August 21-25, 2023.
- Publication date: 2023/08/21
- DOI: http://dx.doi.org/10.18462/iir.icr.2023.0305
Links
See other articles from the proceedings (491)
See the conference proceedings
Indexing
-
Recognition of building occupant behaviors from...
- Author(s) : DENG Z.
- Date : 2021
- Languages : English
- Formats : PDF
View record
-
On Hourly Forecasting Heating Energy Consumptio...
- Author(s) : METSÄ-EEROLA I., PULKKINEN J., NIEMITALO O., KOSKELA O.
- Date : 2022/07
- Languages : English
- Source: Energies - vol. 15 - n. 14
- Formats : PDF
View record
-
Estimating smart Wi-Fi thermostat-enabled therm...
- Author(s) : ALHAMAYANI A. D., SUN Q., HALLINAN K. P.
- Date : 2021/12
- Languages : English
- Source: Clean Technologies - vol. 3 - n. 4
- Formats : PDF
View record
-
Using Deep Learning in Real-Time for Clothing C...
- Author(s) : MEDINA A., MÉNDEZ J. I., PONCE P., PEFFER T., MEIER A., MOLINA A.
- Date : 2022/03
- Languages : English
- Source: Energies - vol. 15 - n. 5
- Formats : PDF
View record
-
A neural-network approach to develop algebraic ...
- Author(s) : LIN L., GAO L., HWANG Y., KEDZIERSKI M.
- Date : 2022/07/10
- Languages : English
- Source: 2022 Purdue Conferences. 19th International Refrigeration and Air-Conditioning Conference at Purdue.
- Formats : PDF
View record