If data from sensors is coupled with the right analytics, it’s possible to spot anomalies and inefficiencies that aid prevention of service failure and enable performance to be optimised. This creates value by giving greater real-time control over costs, and provides insight that informs better collaboration and decision-making between designers and operators.
This has happened at a number of activated sludge treatment works in Australia, which are using real-time data and analytics to gauge the best time to clean aeration tanks and de-clog diffusers. Previously, these operations were undertaken at set intervals. However, with improved insight provided by data, our client has been able to intervene whenever loss of performance becomes an issue, time cleaning operations for when they will cause minimal disruption, and tune operation of the aerators to the actual load, which varies with the rate of wastewater through-flow.
Given that aeration consumes 40%-60% of our client’s overall power costs, there were clear incentives to invest in technology. We developed a cost-benefit calculator for automated decision-making in real time. The calculator highlighted inefficient operation and evidenced payback for replacement of diffusers and control improvements.
We helped to identify opportunities to improve aeration efficiency and achieve power cost savings of A$500,000 per year. Savings, not to be sniffed at.