IDAT7219
Smart Building Technology
1. Basic concepts
2. HVAC controls
3. Advanced HVAC
control
4. Central plant
optimization
5. Smart HVAC
[Powerpoint
file in PDF format]
Videos:
Further
Reading:
References:
- Bhattacharya A.,
2016. Enabling Scalable Smart-Building Analytics,
PhD Thesis in Computer Science, University of California,
Berkeley. https://escholarship.org/uc/item/66d3c6rt
- Behrooz F.,
Mariun N., Marhaban M. H., Radzi M. A. M. & Ramli A. R.,
2018. Review of control techniques for HVAC
systems—nonlinearity approaches based on fuzzy cognitive
maps, Energies, 11 (3) 495. https://doi.org/10.3390/en11030495
- Carrascal-Lekunberri
E., Garrido I., Van der Heijde B., Garrido A. J., Sala J. M.
& Helsen L., 2017. Energy conservation in an office
building using an enhanced blind system control, Energies,
10 (2) 196. https://doi.org/10.3390/en10020196
- Gholamzadehmir
M., Pero C. D., Buffa S., Fedrizzi R. & Aste N., 2020.
Adaptive-predictive control strategy for HVAC systems in
smart buildings – A review, Sustainable Cities and
Society, 63: 102480. https://doi.org/10.1016/j.scs.2020.102480
- Himeur Y., Elnour
M., Fadli F., Meskin N., Petri I., Rezgui Y., Bensaali F.
& Amira A., 2022. AI-big data analytics for building
automation and management systems: a survey, actual
challenges and future perspectives, Artificial
Intelligence Review, 56: 4929-5021. https://doi.org/10.1007/s10462-022-10286-2
- Honeywell, 1997. Engineering
Manual of Automatic Control for Commercial Buildings -
Heating, Ventilating, Air Conditioning, SI Edition.,
Honeywell, Inc., Minneapolis, MN. [HKALL][https://www.academia.edu/9473343/AUTOMATIC_CONTROL_for_ENGINEERING_MANUAL_of_COMMERCIAL_BUILDINGS][https://manualzz.com/doc/61727463/honeywell-automatic-control-si-edition-engineering-manual]
- Mařík K., Rojíček
J., Stluka P. & Vass J., 2011. Advanced HVAC control:
theory vs. reality, IFAC Proceedings Volumes, 44 (1)
3108-3113. https://doi.org/10.3182/20110828-6-IT-1002.03085
- McDowall R. & Montgomery
R., 2011. Fundamentals
of HVAC Control Systems, American Society of Heating,
Refrigerating and Air-Conditioning Engineers, Atlanta, GA. [HKALL]
- Schachinger D.
& Kastner W., 2018. Context-aware optimization
strategies for universal application in smart building
energy management, In 2018 IEEE 16th International
Conference on Industrial Informatics (INDIN), Porto,
Portugal, 2018, pp. 478-483. http://doi.org/10.1109/INDIN.2018.8472000
- Shi Z. &
O'Brien W., 2019. Development and implementation of
automated fault detection and diagnostics for building
systems: A review, Automation in Construction, 104:
215-229. https://doi.org/10.1016/j.autcon.2019.04.002
- Suen A. T. Y.,
Ying D. T. W. & Choy C. T. L., 2021. Application of
artificial intelligence (AI) control system on chiller plant
at MTR station, HKIE Transactions, 29 (2) 90-97. https://doi.org/10.33430/V29N2THIE-2021-0032
- Wang S. K., Lavan
Z. and Norton P., 2000. Air
Conditioning and Refrigeration Engineering, CRC Press,
Boca Raton. [HKALL]
- Wei S., Tien P.
W., Chow T. W., Wu Y. & Calautit J. K., 2022. Deep
learning and computer vision based occupancy CO2 level
prediction for demand-controlled ventilation (DCV), Journal
of Building Engineering, 56: 104715. https://doi.org/10.1016/j.jobe.2022.104715
- Wen J. T. &
Mishra S., 2018. Intelligent Building Control Systems A
Survey of Modern Building Control and Sensing Strategies,
Springer International Publishing, Cham.
[HKALL]
- Zhao D., Watari
D., Ozawa Y., Taniguchi I., Suzuki T., Shimoda Y. &
Onoye T., 2023. Data-driven online energy management
framework for HVAC systems: An experimental study, Applied
Energy, 352: 121921. https://doi.org/10.1016/j.apenergy.2023.121921
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| Created:
Jan 2024 | Update: 27 Jan 2024 |