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.