| I&T Solution |
Dynamic Optimisation of Air Handling Units (AHU) using Physics-guided Machine Learning
(REF : S-0567)
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| Trial Project |
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| Solution Feature |
- Dynamic optimisation of AHU model is built upon the basis of self-trained physics-guided machine learning (PGML) models using actual operating data
- Optimal control settings for AHUs are determined in real-time based on outdoor air conditions, cooling load as well as occupancy level
- Optimal control settings include fresh air/return air damper position, supply air temperature set point and cooling coil valve position
- Level of occupancy can be determined using a wide range of approaches, including CCTV facial recognition and radar technologies
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| Trial Application and Expected Outcome |
- Model calibration is conducted using actual operating data to ensure AHU optimisation performance
- Based on the real-time data including outdoor air conditions, cooling load as well as occupancy level, the optimisation search is performed to determine optimal control settings
- Optimal control settings are sent back to the building management system (BMS) for optimisation
- Key indicators, including levels of thermal comfort, CO2 and energy reduction, are established to evaluate the effectiveness of a project
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| Additional Solution Information |
EMSD_AI FA Energy Saving Control with People Counting.pptx
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| Info on I&T Solution Provider |
| Solution Provider | : | ATAL Building Services Engineering Ltd |
| Address | : | 13/F Island Place Tower 510 King's Road North Point Hong Kong |
| Contact Person | : | Yeung Yau Kwan, Edmond |
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Position | : | Senior Sales Manager
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Tel | : |
2565 3478
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Email | : |
edmondyeung@atal.com
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