DIGITAL TWIN TO AUTOMATE OPTIMISATION AND EMBED EXCELLENCE IN WWTP OPERATIONS
- 1. A co-simulation digital twin for wastewater treatment operations 22 MARCH 2023
- 2. 2 TRILITY Operational sites and people snapshot 2 3 New South Wales 7 8 Queensland 4 7 Victori a 4 Tasmania 9 4 South Australia 3 6 Western Australia 2 7 New Zealand 0 Australian Capital Territory
- 3. 3 3 Sustain optimal performance Prescribe best course of action Detect changes automatically DECISIONS MADE CLEAR Sustainable operational excellence Change in conditions New process settings required Provide update from KDX application Automatically identify underperforming processes or assets Digital tool recommends the best course of action Update control strategies dynamically while reducing costs and risk
- 4. 4 4 Decisions made clear Defining a new digital landscape We view utility operations as a whole, providing the confidence to solve common problems with process twins and automation. Source water quality and climate resilience Effective water treatment processes that optimize chemical usage, filter efficiency, and WQ compliance management. Demand forecasting, network leakage detection and water age management Resilience to water sources impacted by climate change and emerging contaminants. Wastewater resource recovery, optimising nutrient removal and reducing greenhouse gas emissions. Water treatment and production Wastewater treatment sustainability Networks, water quality, and customer satisfaction
- 5. 5 Data quality and management Influent quality and loading variability Operator capacity and skills Energy consumption costs Residuals The increasing complexity of managing wastewater treatment DECISIONS MADE CLEAR
- 6. 6 Data quality and management The increasing complexity of managing wastewater treatment DECISIONS MADE CLEAR • Data storage and retrieval required for billions of timeseries data points. • Information and cybersecurity costs and complexity for distributed and cloud-based systems. • Aging solutions lacking modern user interfaces and experiences for ease of use
- 7. 7 Influent quality and loading variability The increasing complexity of managing wastewater treatment DECISIONS MADE CLEAR • WWTP capacity issues with growing urban populations. • Operators under resourced to identify and adapt to toxic shock events. • Lack of regular or comprehensive influent WQ monitoring programs.
- 8. 8 Operator capacity and skills The increasing complexity of managing wastewater treatment DECISIONS MADE CLEAR •Tighter regulations on performance and effluent quality. •Age of assets and increased maintenance. •Utility skills retention with an aging workforce. •Additional pressure to use more and more systems and processes, often with limited support.
- 9. 9 Energy consumption costs The increasing complexity of managing wastewater treatment DECISIONS MADE CLEAR • The water sector accounts for 4% of total energy consumption, with highly energy-dependent wastewater treatment plants (WWTPs) accounting for 25% of the total energy use • Globally, almost 400 billion m3 of wastewater is produced annually, and it is expected to increase by 25 and 50% by 2030 and 2050, respectively.
- 10. 10 Energy consumption costs and net zero The increasing complexity of managing wastewater treatment DECISIONS MADE CLEAR • WWTPs in the USA generated 20 million metric tons (MMT) CO2-eq in 2017. • The energy needed for a typical domestic WWTP employing aerobic activated sludge processes and anaerobic digestion (AD) is 0.6 kWh per m3 of wastewater treated • About half of which is used for providing electrical energy to sustain aeration basins.
- 11. 11 Residuals management The increasing complexity of managing wastewater treatment DECISIONS MADE CLEAR • Increased transportation and disposal costs. • Increased biosolids management regulations and requirements. • Increasing industry movement to resource recovery and a need for optimised production and recovery techniques and solutions.
- 12. 12 Bioreactor health DECISIONS MADE CLEAR How do we balance optimal bioreactor health energy use and operator time with changing conditions and goals? Is there a better way to think about bioreactor health and managing process complexity?
- 13. 13 What options do we have? DECISIONS MADE CLEAR Offline PBSE models Additional instrumentation Training and development of staff Advanced energy management Realtime DPTs and machine learning Capital upgrades
- 14. 14 14 Why now for digital process twins (DPTs)? • No or minimal retroffiting of existing plant. • New powerful mathematical optimisations and solvers have been developed. • ML capable of real-time process optimisation has advanced rapidly in the last 10 years. • Numerical simulation performance and vastly increased computing power and efficiency. • Improved economics with reduced cost of ownership and increased availability. DECISIONS MADE CLEAR
- 15. 15 15 Why digital process twins (DPTs)? DECISIONS MADE CLEAR
- 16. 16 KDX operations platform • Provide a cost effective and scalable DPT platform. • Decision support tools co-designed with operations teams. • Designed from the ground up to meet information security needs for utility infrastructure. DECISIONS MADE CLEAR
- 17. 17 17 Victor harbor WWTP • Operated by TRILITY since 2006 • Proof of concept plant for a scaled dynamic co-simulation environment 5MLD Membrane bioreactor WWTP DECISIONS MADE CLEAR Units 50th percentile 90th percentile BOD5 mg/L 5 10 SS mg/L 1 2 NH3-N mg/L 1 2 TN mg/L 5 10 TP mg/L 0.05 0.1 E. Coli E.c/100ml 1 10
- 18. 18 Real-time co-simulation DECISIONS MADE CLEAR ODE + ML Surrogate Calibration and validation campaign with dynamic WWTP real-time data ingestion Physics based simulation engine Self-calibrating process twin for the WWTP Physics based simulation engine
- 19. 19 Dynamic calibration of the DPT • Multi-phase approach to quantifying and reducing uncertainty: long-term averages down to dynamic, near-term data. • Calibration can be adjusted based on real- time and/or varying data quality. • Historical and real-time ‘soft-sensors’ and insights can then be generated. DECISIONS MADE CLEAR Multi-scale calibration to reduce uncertainty
- 22. 22 Benefits of real-time DPT calibration • Soft sensing of Influent Water Quality and in-reactor ‘hidden’ states. • Early detection of toxic-shock or equipment failure. • Long-term trending of parameters. • Testing and validation of assumptions. • Single- and/or multi-objective optimization.
- 23. 23 Physics-Informed Artificial Intelligence Systems DECISIONS MADE CLEAR
- 24. 24 Physics-Informed Artificial Intelligence Systems DECISIONS MADE CLEAR • Pure physics relies heavily on quality input data to predict ‘real’ results, slow to recalibrate, need expertise to build and develop. • Pure AI models need extensive amounts of data in order to capture full system dynamics. • Surrogate models such as PINNs, Bayesian ODEs etc can bridge this gap.
- 25. 25 Using AI surrogates DECISIONS MADE CLEAR
- 26. 26 26 Scenario exploration ~20% Power consumption reduction expected for aeration. DECISIONS MADE CLEAR
- 27. 27 27 Scenario exploration ~20% Power consumption reduction expected for aeration. DECISIONS MADE CLEAR
- 28. 28 28 What’s next KDX Aer+ software release v3.0 • MBR / SBR in April 2023. • Automated toxic shock identification • Event engine and mobile notifications DPT Commissioning WWTPs • Rotorua WWTP 2023 • Customer WWTPs x3 2023 • Upper South Creek 2025 Release updates for improved solvers DECISIONS MADE CLEAR
- 29. Thank you