Hong KongReal estate2021 – ongoingSun Hung Kai Properties
Machine-learning chiller optimisation at V city
V city's chiller retrofit shortened monitoring intervals to 30 seconds
Problem
V city's chiller plant needed closer performance monitoring to identify efficient operating settings. Its previous data-monitoring interval was 15 minutes.
Approach
The mall installed an optimisation system combining machine learning with a digital twin. ATAL Building Services Engineering was the contractor. The system filtered invalid readings and compared chiller performance to support operating and maintenance decisions.
Results
Takeaway
The retrofit improved the frequency and quality of operating data alongside its optimisation functions. The monitoring interval alone did not measure energy savings.
Categories
- Size
- Large enterprise
- Industry
- Real estate
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and MLOptimization
- Adoption
- Vendor solution
- Evidence
- Company's own claim
Sources
Source summaries
The V city case described an installed machine-learning and digital-twin chiller system. Reported benefits included more frequent monitoring and correction of sensor drift.
Full details are in the original sources.