Background image: Melbourne Case Study Banner

Case Study: Model Predictive Control for Energy and Water Conservation

How we helped Melbourne Water save billions of liters of water each year with Model Predictive Control

The Thomson Reservoir feeds into one of the largest water supply networks in Australia. Operated by Melbourne Water, it is at the core of water supply for the city of Melbourne and the surrounding suburbs. To ensure the Thomson river environment downstream of the dam is protected, the flows in the river have to be controlled and optimized so that the correct amount of water is released at all times.

If too much water is released, the river environmental conditions are not impacted, but the source water is wasted. If too little is released, the environmental conditions are impacted and Melbourne Water fails to meet its minimum compliance requirements.

Kalypso and Rockwell Automation worked with Melbourne Water to help regulate water leaving the Thomson Reservoir with increased efficiency and precision.

Real Results

  • Conservation — 2 billion liters per year in water savings, exceeding the initial goal

  • Cost savings — ongoing cost savings, and reduced dependence on desalination

  • Compliance — 10% increase in environmental compliance

The complexity of the network, paired with factors like lag time and multiple environmental variables made this system a perfect candidate for model predictive control (MPC).

Protecting infrastructure — As precious as gold or oil - the control of water being released for human, livestock or environmental use is critical for such a scarce commodity.

Accounting for multiple variables — Factors like farmers purchasing water for irrigation downstream, rainfall runoff and evaporation all make it more difficult to predict flow and water levels.

Calculating for lag time — There is a time lag of up to 10 Hrs from changes made to release flows at the dam, to when those changes are seen at the farthest compliance point.

Supporting compliance and water quality — As a public utility and a purveyor of a critical natural resource, Melbourne Water puts water conservation at the core of its business.

While the water industry is relatively mature when it comes to automation and system optimization, quality, process variability, outages and downtime are still persistent challenges.

The complexity of calculations, the duration of focus and the speed and precision required are poorly suited to human capabilities. MPC applies a data science layer on top of existing regulatory controls to continuously monitor and predictively optimize process behavior.

MPC analyzes a set of variables (e.g. flows from tributaries, rainfall, evaporation, irrigation consumption, etc.) in real time and continuously, predicting and driving the set point adjustments to maintain optimal system function, removing the strain of extended observation from conventional operation eliminating the root cause of variability, outages and downtime.

Background image: Melbourne Case Study Section Drop

Model predictive control reduces process variability to achieve plant obedience and manages the uplift within process constraints

The outputs from the Pavilion8 system are adjustments to set points in the existing regulatory control system

The normal variability present in any operating process results in a standard deviation from desired control targets

With model predictive control we reduce the variability and standard deviation

Once the process is under tighter control we're able to operate closer to process specification limits

Melbourne Water saved billions of liters of water every year with model predictive control

Our work made it possible to save 2 billion liters of water annually, conserve energy and reduce strain on the workforce while improving compliance. We helped Melbourne Water set the bar for autonomous operations and responsible stewardship over a critical natural resource.

Thought Leaders