HDSR optimises sludge treatment & reduces chemical consumption

The challenge

Optimising sludge treatment while lowering operational costs and reducing chemical usage

Accounting for up to 50% of overall costs at wastewater plants, sludge treatment is expensive. It also has a significant environmental impact – due both to the chemical consumption it requires and the CO2 and methane that the process releases. In addition, it is labour-intensive and difficult to optimise without automation. 
Working in partnership with Royal HaskoningDHV, HDSR was searching for a digital solution to continuously optimise sludge treatment and lower staffing costs while reducing polymer consumption and emissions at its Utrecht plant while it was under construction. 

The solution

Leveraging machine learning, real-time data and domain knowledge to optimise logistics and processes

After extensive research and piloting, the Royal HaskoningDHV team found that optimising sludge transport and introducing a dewatering installation (leveraging AI, predictive controls and real-time monitoring) would improve overall performance and reduce operational costs. As a result, our engineers recommended Twinn Aqua Suite software, which HDSR (and its contractor GMB) implemented in 2018. 

HDSR uses 2 Twinn Aqua Suite capabilities:

• Sludge transport – leverage AI and real-time data to optimise sludge transport from external wastewater treatment plants to the Utrecht sludge line. By generating everyday transport advice, the software decides which locations to transport from and how many vehicles are required – creating easy-to-follow daily plans for HDSR’s truck drivers.
• Process optimisation – We implemented this simultaneously with sludge transport. Leveraging machine learning, Twinn Aqua Suite analyses centrate quality, dewatering data and historic performance results to optimise dewatering and polymer dosage at the plant. 

By optimising the flow through the entire sludge line, we have provided stability while reducing unwanted retention times. HDSR operators no longer have to predict the amount of incoming external sludge to the plant. And in combination with actual buffer level data, Twinn Aqua Suite determines the optimal output, maintaining a constant flow throughout sludge treatment.

The impact

Reduced chemical usage, optimised processes and lower costs

Twinn Aqua Suite has delivered strong results at HDSR’s Utrecht plant. It has enabled HDSR to reduce staffing for sludge dewatering by between 50 and 80%. In addition, it has helped decrease polymer consumption by up to 20%, a reduction in CO2 production of up 80 tonnes per year (equivalent to driving 500,000 kilometres in a standard diesel car). 
“Twinn Aqua Suite is the perfect solution for HDSR because it uses self-learning algorithms to predict the volume of sludge and its quality, and to self-regulate thickeners, centrifuges, chemical dosing and sludge transport,” said Melchior Schenk of Twinn Aqua Suite. “Due to the integrated approach and predictive, adaptive management of the entire sludge line, we’ve enabled HDSR’s Utrecht plant to save hundreds of thousands of euros per year.”

Thanks to Twinn Aqua Suite’s self-learning functionality, the sludge line adjusts to changes in composition, demographic trends and climate changes 24/7 – a level of optimisation that was nearly impossible for plant staff to reach alone.

“One of the most helpful features for process operators is the years of domain knowledge the software has,” said Erik Rekswinkel, Wastewater Engineer & Process Operator at HDSR. “Twinn Aqua Suite supplies predictions which save operators time because they don’t have to do the same work manually every day. I couldn’t have calculated it better. And we couldn’t carry out the control 24/7 which Twinn Aqua Suite does” 

Hans van de Meent, Process Operator at HDSR, agrees that the software’s impact has been significant: “Thanks to Twinn Aqua Suite, you can see at a glance what is present in the buffers and what the required discharge is.”