The Chilled Water Plant Optimisation Project involved using the latest machine learning and simulation techniques to improve the control logic of the International Terminal 1 chiller plant and secondary pumping system.

The project achieved a 33.4% increase in efficiency, reducing energy consumption by 890,094 kWh and cutting GHG emissions by 704 tCO2 over nine months, through improved efficiency. The overall annual project reduction in energy consumption was 1,742,000 kWh, equivalent to 1,377 tCO2.

The Chartered Institution of Building Services Engineers judges were highly impressed with this project, noting its ability to achieve significant energy savings in the first year while continuing to improve the chiller system’s efficiency. They praised the innovative use of digitalisation of existing equipment and controls systems, tied together with real-world data.

This project highlights the transformative potential of advanced data analytics and machine learning for HVAC optimisation, delivering scalable solutions for energy efficiency.

The judges commended the high standard of entries in this category, which showcased exceptional approaches to decarbonisation and energy optimisation. While many outstanding submissions did not make the shortlist, all demonstrated significant innovation and impact.

“It is good to see considerable progress in the digitalisation of the O&M sector,” they said. “This has the potential to open up new avenues of data and insight into building life-cycles to enable improvements in user experience and compliance in real-time.”

The project was undertaken in a close partnership between A.G. Coombs Advisory and Exergenics, working with the Sydney Airport team to achieve their ambitious sustainability targets.