Filip H.A. Claeys, DHI Software Products, Denmark

Optimizing industrial water networks with the WQMT

Henrik Birch, DHI Solutions, Denmark

Mónica de Gracia, ATM / Praxair, Spain

René Jurgens, TNO, the Netherlands

Izaro Lizarralde, CEIT, Spainfhcl@dhigroup.com

Filip H.A. Claeys, DHI Software Products, Denmark

Optimizing industrial water networks with the WQMT WESTforINDUSTRY

Henrik Birch, DHI Solutions, Denmark

Mónica de Gracia, ATM / Praxair, Spain

René Jurgens, TNO, the Netherlands

Izaro Lizarralde, CEIT, Spainfhcl@dhigroup.com

WESTforINDUSTRY ?

3

• Software framework for representing and solving water quality issues in industrial water networks

• Currently still under development in the scope of the AquaFit4Use project

• Previously known as WQMT - “Water Quality Management Tool”

• Based on DHI’s Tornado engine, and user interface modules from the WEST commercial WWTP modeling & simulation tool

• Prototypes used by project partners in support of case studies

Questions answered ?

4

• What is effect of...

– ... changes in network topology?

– ... changes in discharge limits?

– ... changes in water source quality?

– ... changes in treatment options?

– ... changes in industrial processes?

– ... changes in operational parameters?

– …

Objectives ?

5

• Management of information on water network blocks

– Behavior

– Constraints

• Creation of visually appealing graphical layouts of water networks

• Simulation of water networks

– Computation of flows & component concentrations

– Computation of objectives on the basis of data aggregation

– Check for constraint violations

• Optimization of water networks

Competing tools ?

6

Spread-sheets

Pinch Analysis

Process Simulators

WEST for INDUSTRY

Network topology � �

Simulation � � �

Optimization � � (�) �

Intuitive � � �

Specialized � �

Realistic models � � �

Openness � � (�) �

AquaFit4Usemethodology

�

Visualization

7

Architecture

8

Model Representation

9

• Static representation of behavior and “cost” (objectives)

• Specification in Modelica language

– Popular product-independent modeling language

– Object-oriented

– Based op equations

• Final models are programmatically composed on the basis of automatically generated sections and custom sections

• Models can be linked to external code for computing chemical equilibria (cf. pH):

– Automatically generated dedicated custom C code

– PHREEQ-C engine

Simulation

10

• Set parameters

• Select subset of components for output

• Execute simulation

• If needed, efficient executable model is created silently

• Results

– Flows & component concentrations

– Objectives (investment cost, operational cost, …)

– Constraint violations

Optimization

11

• Principle: automatic evaluation of predefined alternatives

• Determine optimization variables

– Selection of parameters

– Specification of values for each parameter

• Manually

• Automatically through spacing between bounds or samplingfrom statistical distributions

• Generate runs for all combinations of parameter values

• Optionally: Manually add / remove / modify runs

• Execute runs & perform ranking according to objectives

Optimization

12

• Typical ranking

– Grouping on basis of numerically erroneous / error-free runs

– Grouping on basis of number of constraint violations

– Sorting on basis of objective values

• Selection of run that has no numerical errors, least number of constraint violations and best objective value

• Export of results to text or Excel file for post processing

WESTforINDUSTRY vs. WEST ?

13

WESTforINDUSTRY WEST

Focus Industrial networks Domestic wastewater

Model type Static Dynamic

Modeling language Modelica MSL

Model definition At run-time A priori

Component definition At run-time A priori

Range definition At run-time A priori

Model repository Central, Local Local

Complex experiments SA SA, PE, LSA, GSA, UA

Output Tables Tables, Plots

Visualization on layout Yes No

Case studies

14

• Generic

– Benchmark Water Network

• Food Industry

– Unilever - Ben & Jerry’s (Hellendoorn, NL): Ice cream factory

– Alpro (Wevelgem, B): Soya products plant

• Paper Industry

– Holmen (Madrid, E): Recycled paper production plant

• Chemical Industry

– Perstorp (Perstorp, S): Polyol production plant

Case study: Unilever - Ben & Jerry’s

15

Case study: Unilever - Ben & Jerry’s

16

• Situation

– Construction of Anaerobic Digester for treating waste water

– Construction of Living Machine (ponds with plants) for treating waste water

– Questions about potential use of rainwater as alternative water source

• Scenarios

– Discharge of Living Machine effluent to surface water (river Regge)

– Use of Living Machine effluent in cooling tower

– Use of rainwater in transport washing

– Use of rainwater in toilet flushing

– Use of Living Machine effluent in COP processes

Case study: Unilever - Ben & Jerry’s

17

• Conclusions

– Living Machine effluent can be conditionally discharged to river

– Infiltration is possible with Living Machine effluent

– Chemicals and salt content of the CT can be bottleneck for infiltration

– Softening of groundwater is needed for use in the CT

– Living Machine effluent can be conditionally used in the CT and in COP processes

– Treatment of rainwater is required for use in transport washing to prevent growth of bacteria

– Rainwater can be used in toilets

Case study: Alpro

18

Case study: Alpro

19

• Situation

– Water used from 3 water sources with variety in composition, most notably in hardness

– Water softened by ion exchangers and reverse osmosis

– Softening requires frequent regeneration of resin

– Currently leading to precipitation problems

– Water re-use is desired in general

• Scenarios

– Less extensive softening

– Softening with FACT

– Use of WWTP effluent for DWS processes

– Use of WWTP effluent for cooling towers

– Use of sealing water in DWS processes

– MBR treatment

Case study: Alpro

20

• Conclusions

– 85-89% softening is sufficient for the soft water processes for respectively 27 °F and 45 °F city water. The steam boiler requires > 97/98% softening which can be done by a dedicated softener.

– Bypassing the IX regenerate and RO concentrate at the WWTP will drastically reduce the chances of scaling in the water system.

– The required softening of the city water for the DWS processes can be achieved using FACT.

– MBR treatment is needed to make the WWTP effluent suitable for use in the DWS processes

Case study: Alpro

21

• Conclusions

– Reuse of the WWTP effluent in the cooling towers is possible for the 27 °F city water at 90% softening. For 45 °F city water near 100% softening is needed (not realistic).

– The sealing's effluent can be used in the DWS processes.

– No pathogens (Legionella, E-Coli, Enterococci) were found in the various water streams.

– The WWTP effluent also does not contain any pathogens. However, to ensure safe use in all cases disinfection before reuse is strongly advised.

Case study: Perstorp

22

Case study: Perstorp

23

Case study: Holmen

24

Case study: Holmen

25

Gravity table

Sludge

PM 62

DAF 1

LOOP 1

DAF 2

Product

DAF 3

Cooling

tower

Effluent

MBBR3

DAF 4

Evaporation and

losses

LOOP 2

Water steam

MBBR1

Cooling

processes

MBBR4MBBR2

Clean water

Process water (<1g/l)

Product line

Waste line

2 3 4

5

6

7

8

9

10

11

12

14Storage

Boilers

Cooling

water

tank

13

De DIP2/3

1Drum

Pulper2'

Case Study: Holmen

Case Study: Holmen

Existing WWTP

Enhance existing WWTP

New WWTP

1

2

3UASB MBR RO UV

Case Study: Holmen

( )

NKQ

NQQTSS

NOP

LS

NIC

COST

FW

w

ww

treati

i

treatnewi i

i

·365···411.1

·365··1510

··200

·365·

·

6+

+

+

+

=

∑

∑

=

=

Investment

cost

Operational

cost

Cost associated with

sludge treatment

Drinking

water

Case Study: Holmen

ConceptScenario 1 Scenario 2 Scenario 3

IC (€) OP (€/d) IC (€) OP (€/d) IC (€) OP (€/d)

Drinking water --- 19754 --- 7986 --- 6451

Sludge production --- 156219 --- 158227 --- 140568

MBBR --- 955 --- 955 --- ---

DAF --- 53 --- 53 --- ---

UASB --- --- --- --- 2593192 34

MBR --- --- --- --- 3643882 229

RO --- --- 832085 566 1110224 188

UV --- --- 195065 160 189863 156

Total cost in 20 years 1291.9 M€ 1227.0 M€ 1085.2 M€

Conclusions

30

• WESTforINDUSTRY is a powerful tool for the optimization of industrial water networks described by detailed static models

• It combines features separately found in other tools, under the hood of a modern and visually appealing user interface

• Cases in various industrial sectors have demonstrated the usefulness of the tool

• Tool is mainly interesting for consultants performing full-fledged case studies, or for end-users (industries) doing smaller scale scenario analyses and/or for communication between experts and management

• DHI will carry WESTforINDUSTRY further commercially after conclusion of AquaFit4Use project

Questions ?

Alpro ���� René Jurgens, TNOUnilever ���� René Jurgens, TNOPerstorp ���� Henrik Birch, DHI Holmen ���� Izaro Lizarralde, CEIT