Operational performance of an Air Handling Unit: insights from a data analysis

Author:

Noussan Michel,Carioni Giovanni,Degiorgis Luca,Jarre Matteo,Tronville Paolo

Publisher

Elsevier BV

Reference12 articles.

1. Verbert, K., Babuška, R., Schutter, B.D.. Combining knowledge and historical data for system-level fault diagnosis of {HVAC} systems. Engineering Applications of Artificial Intelligence 2017;59:260–273. URL: http://www.sciencedirect.com/science/article/pii/S095219761630255X. doi:http://dx.doi.org/10.1016/j.engappai.2016.12.021.

2. Yan, R., Ma, Z., Kokogiannakis, G., Zhao, Y.. A sensor fault detection strategy for air handling units using cluster analysis. Automation in Construction 2016;70:77–88. URL: http://www.sciencedirect.com/science/article/pii/S0926580516301261. doi:http://dx.doi.org/10.1016/j.autcon.2016.06.005.

3. Dey, D., Dong, B.. A probabilistic approach to diagnose faults of air handling units in buildings. Energy and Buildings 2016;130:177–187. URL: http://www.sciencedirect.com/science/article/pii/S0378778816306958. doi:http://dx.doi.org/10.1016/j.enbuild.2016.08.017.

4. Kusiak, A., Zeng, Y., Xu, G.. Minimizing energy consumption of an air handling unit with a computational intelligence approach. Energy and Buildings 2013;60:355–363. URL: http://www.sciencedirect.com/science/article/pii/S0378778813000741. doi:http://dx.doi.org/10.1016/j.enbuild.2013.02.006.

5. Cetin, K.S., Kallus, C.. Data-driven methodology for energy and peak load reduction of residential {HVAC} systems. Procedia Engineering 2016;145:852–859. URL: http://www.sciencedirect.com/science/article/pii/S1877705816302156. doi:http://dx.doi.org/10.1016/j.proeng.2016.04.205; {ICSDEC} 2016–Integrating Data Science, Construction and Sustainability.

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