Model Pure -Optimises Nutrient Removal from Wastewater and Sludge Supply to Sludge Line
Aquasuite PURE is a machine learning and AI solution for the control and optimisation of wastewater treatment works. It uses the proven Aquasuite AI algorithms to predict influent flow and load, enabling its virtual operator to control the wastewater treatment works with maximum efficiency and effectiveness.
Energy and Nitrogen reduction
With Aquasuite PURE, nutrient removal and the energy and chemical use of your wastewater treatment process are optimised. Aquasuite PURE has been proven to deliver energy reduction of up to 18% and reduction in Total Nitrogen by up to 50.7%.
Focus on technical tasks
Aquasuite PURE’s virtual operator maintains stable and compliant control at all times of the day and year. This allows skilled operators to focus on specialist technical tasks rather than day-to-day operation of the WwTP.
- Reduces costs
- Reduces risk of not meeting quality regulations
- Resilient against external influences
- Decreases dependency on skilled operators
- Ultrafiltration process in wastewater treatment
- Correct sludge distribution and up to 40% less energy use (on return sludge transport)
Aquasuite PURE uses existing sensors and instruments to gain a complete understanding of the wastewater treatment process. It uses machine learning and external factors such as weather, public holidays, etc., to make a very accurate prediction of influent flow and load. Aquasuite PURE additionally learns the relationships between key treatment stages such as aeration, influent flow & load and required effluent quality.
The system uses this clear oversight of the processes to become a virtual operator for the wastewater treatment plant. It uses the learnt relationships between each of the processes and the required effluent quality to provide predictive control set points for each process, based on the predicted influent flow and load. This drives the most efficient combination of processes, whilst still achieving the required effluent quality. Aquasuite further uses a self-learning algorithm to iteratively improve its set-point determination which, together with the AI predictions, results in very stable and energy efficient wastewater treatment.
Aquasuite collects data from numerous data sources and automatically provides control set points to assets via existing SCADA or PLC control methods. Its aim is to be hardware agnostic and work with existing sensors, data collection and control systems.