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Model based optimization of the control of pellet softening process in PWN

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17 diapositives · 347 Views · Jul 13, 2014

Model based optimization of the control of pellet softening process in PWN. Intermittent Presentation 1 & Working Progress Xiaoyu Yuan Supervisor: Ignaz Worm; Luuk Rietveld. Introduction. Research scope: Softening reactors in Wim Mensink and partial flow from Heemskerk I

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Model based optimization of the control of pellet softening process in PWN
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  1. Model based optimization of the control of pellet softening process in PWN Intermittent Presentation 1 & Working Progress Xiaoyu Yuan Supervisor: Ignaz Worm; Luuk Rietveld

  2. Introduction • Research scope: Softening reactors in Wim Mensink and partial flow from Heemskerk I • Objective of this research: (1) Calibration and validation for the model and historical data. (2) Developing different control strategies for the operation of softening reactors and choosing the robust ones

  3. Current work procedure • Process study of Wim Mensink for this research • Softening process study • Studying of previous softening research work in Weesperkaspel • Analysis of dynamic model and current control strategy in Stimela for PWN • Effluent water quality analysis for Heemskerk I

  4. Water intake from river IJssellake Pretrated at WPJ 10% of RO permeate mixing with Wim Mensink from HK I discharging into dune area Decription of water treatment process in PWN

  5. Water treatment process in Wim Mensink • Flow proportion for FB1 and FB2 is 2:1. • CO2 is dosed in the first cascade of aeration. • Flow in HK I is mixed with flow in FB1 and FB2 together.

  6. Water quality standard in PWN

  7. Softening reactors • 6 reactors in total with each design capacity 500 m3/h • Usually 5 of 6 reactors in operation

  8. Reactors switch on with the following amounts: 450; 666; 1,700; 2,000; 2,666 and 3,100 m3/h Extra flow goes through bypass pipe. Softening reactors

  9. Softening reactors Reactors switch off with the following amounts: 2,500; 2,300; 1,750; 1,100; 500 and 400 m3/h Extra flow goes through recirculation pipe.

  10. Intitial water quality directly after RO process High acidity Low hardness Low saturation index Final water quality after treating with different process Step 1: adding process water - Increasing hardness Step 2: adding NaOH - Increasing pH Step 3: dosing CO2 - Improving saturation index Effluent water quality analysis for Heemskerk I

  11. Developed by TU DELFT and DHV based on Simulink function in Matlab Designed for water quality modelling Off-line control and simulating operational process Stimela Model

  12. Stimela Model applied in this research

  13. Hydraulic model in Epanet Filter building 1 Softening reactors Filter building 2

  14. Modelling fluidised bed - Dividing reactors into several layers Each layer consists of: Mass of calcium carbonte Mass of grains Bed porosity Calibration and validation work for pellet size Laboratory scale Pilot scale Full scale Previous main work in Weesperkaspel

  15. Simulated optimizing results over pellet size aned bypass flow Previous main work in Weesperkaspel

  16. Next steps • Historical data analysis for flow, pH, SI, total effluent hardness. • Calibration and validation work for the data from 2006 to 2008. • Developing new control strategies with different operational conditions and analysing the results. • Selecting the most robust strategies for PWN and suggestions for other ones.

  17. Thank you for attention! Questions???