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Quality control for groundwater treatment plant Oldeholtpade

Quality control for groundwater treatment plant Oldeholtpade. Wilbert van de Ven , Simon Bakker, Rein Wuestman, Idsart Dijkstra, Matthew McEwan, Simon Mazier, Bart Bergmans, Petra Ross, Luuk Rietveld, Kim van Schagen. Vitens. Problem definition. Plants are designed conservatively

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Quality control for groundwater treatment plant Oldeholtpade

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  1. Quality control for groundwater treatment plant Oldeholtpade Wilbert van de Ven, Simon Bakker, Rein Wuestman, Idsart Dijkstra, Matthew McEwan, Simon Mazier, Bart Bergmans, Petra Ross, Luuk Rietveld, Kim van Schagen

  2. Vitens Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  3. Problem definition • Plants are designed conservatively • Effect of quantity adjustment on water quality unknown • Ex(t/p)ensive monitoring program required Water quantity: Real-Time Water quality: Mainly Lab and off-line Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  4. Develop soft-sensors for water quality Translate all data into information on all levels Advice plant operators Simulation tool for operators New design rules for future plants Aims of the project Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  5. Philosophy Dashboard pH Turbidity Cond UV Real-time online sensoring Ω, ΚT, d, H Information Real-time proces monitoring Data-driven and white box modelling CH4 NH4 Mn Fe Proces operator Ca Mg Laboratory analysis

  6. Air Aeration air RSF RSF IEX color removal Decarbonisation pellet softening White box modelling Data-driven modelling Pilot location: WTP Oldeholtpade groundwater

  7. First step: Assessment of WTP • Identify all the data streams • RTPM data • LIMS data • Quality of the data • Expose operator experience • Statistical analysis of the data • Answer the question: What is the added benefit of information over data? Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  8. Example: pH measurement validation with ArchitectMV Status of the process Anomaly in one or someof the sensors? Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  9. Example 2: Filtration-backwash modelling Filtrationresistance Initial resistance Fouling rate Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  10. Estimation of raw water quality Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  11. Estimation of raw water quality Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  12. Modeled pH change after plate aeration Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  13. Modeled methane removal with plate aerators Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  14. Sensors Sensors Sensors Online sensors for WTP for full modeling Development of sensor boxes Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  15. Summary • Plant-wide soft sensor for water quality • Much information revealed by smart data handling • Data quality is an issue • Next step in the project • Development of SLIMM-boxes • Define modeling structure • Integrate Stimela models into ArchitectMV Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

  16. Suggested Approach ArchitectMV Statistical data analysis White box and/or data driven modeling Voettekst aanpassen via Menu->Beeld->Koptekst en voettekst

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