Australian public water utility Melbourne Water is using artificial intelligence and machine learning to cut electricity costs in its water treatment plants.
Efficiency is generally seen as a key marker of a smart city, and this is certainly the case in the Australian city Melbourne. Its public water utility, Melbourne Water, is now testing a custom-developed artificial intelligence (AI) programme that coordinates pump configuration with the amount of treated water required at any given time – without any human intervention. The settings are then applied in real time.
“The Python programme is able to utilize our historical data to determine the most energy efficient combinations of pumps and the associated speeds to run them at in order to achieve the necessary flow rate,” said Melbourne Water Automation Team leader Russell Riding. It is powerful enough to consider a wide range of factors unique to the water supply system, including reservoir level, available pumps and past performance.
Cybersecurity was an important consideration when trialling the system, added Riding. “The AI is stored on a computer which is not connected to the broader Melbourne Water network, or the internet. This is best practice to ensure that cyber security risks are minimized.”
The project is expected to reduce Melbourne Water’s pump station energy costs at its Winneke treatment plant by around 20 per cent per year. Winneke is one Melbourne’s major water treatment sites, with some 350 million litres of water moves through the plant every day before being distributed to millions of homes and businesses around the city.
“We’re currently commencing testing with Python on another pump station with different requirements to find out if we can replicate the same kind of results that have been achieved at Winneke,” said Riding.
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