a benchmark simulation model to describe plant …a benchmark simulation model to describe...

Div. of Industrial Electrical Engineering and Automation (IEA) Lund University, Sweden

A Benchmark Simulation Model to describe plant-wide phosphorus

transformations in WWTPs

Dr Ulf Jeppsson

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Watermatex2015, June 14-17, Surfers Paradise, Queensland, Australia

Acknowledgements To all co-authors:

–  Dr Xavier Flores-Alsina, Technical University of Denmark

–  Dr David Ikumi, Univ. of Cape Town, South Africa

–  Christian Kazadi-Mbamba, Univ. of Queensland, Australia

–  Kimberly Solon, Lund University, Sweden

–  Dr Stephan Tait, University of Queensland, Australia

–  Chris Brouckaert, Univ. of KwaZulu-Natal, South Africa

–  Dr George Ekama, Univ. of Cape Town, South Africa

–  Dr Damien Batstone, University of Queensland, Australia

–  Dr Krist Gernaey, Technical University of Denmark

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© Dr Ulf Jeppsson, 2015 Lund University, Sweden

A Benchmark Simulation Model to describe plant-wide phosphorus transformations in WWTPs

Outline

§  Introduction §  Methodology

§  New and upgraded models §  Model integration §  Additional BSM modifications

§  Results §  Discussion §  Conclusions §  Perspectives

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Introduction

§  BSM work started as part of an EU COST action in 1997 §  IWA Task Group on Benchmarking of Control Strategies

for WWTPs initiated in 2005 §  Today finalized versions of BSM1, BSM1_LT, BSM2, the

influent wastewater generator model, ADM1 with PCM and more – available for free

§  IWA Scientific & Technical Report no. 23 (2014) §  500+ publications related to BSM §  Many ongoing BSM extension (GHG, P, S, X, PCM etc)

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Benchmark Simulation Models

Effluent Quality Index Operational Cost Index Risk Index

C, N removal

C, N, P removal

BSM1 BSM1_LT BSM2 BSM2-P

Schematic representation of the BSM2 plant (Gernaey et al., 2014).

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New/upgraded bio(chemical) models Activated Sludge Model No. 2d (ASM2d)

§  biomass decay rate are electron-acceptor dependent

§  inorganic suspended solids added (XTSS) §  chemical precipitation replaced

Anaerobic Digestion Model No. 1 (ADM1) §  with bio-P (Ikumi et al., 2014) §  XC is omitted –> towards ADM2 §  hydrolysis parameters are adjusted

Physico-chemical Model (PCM) §  pH model (Batstone et al., 2012;

Flores-Alsina et al., 2015)) §  ion speciation/pairing model (Solon

et al., 2015) §  precipitation model (Kazadi-

Mbamba et al., 2014)

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Model integration Activated Sludge Model No. 2d (ASM2d)

Anaerobic Digestion Model No. 1 (ADM1)

Physico-chemical Model (PCM)

ASM – PCM interface

ADM – PCM interface

ASM – ADM interface

using continuity-based interfacing models (Vanrolleghem et al., 2005)

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New influent characteristics

0 1 2 3 4 5 6 75

6

7

8

9

10

11

12

13

14

15

t (days)

PO4 -3

Influent Generator

also reasonable dynamics of all anions and cations included

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New BSM2-P plant layout

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New/extended evaluation criteria

EQI Effluent Quality Index

OCI Operational Cost Index

§  include phosphorus-related compounds

§  account for use of chemicals and their impact on sludge production

§  benefit of nutrient recovery (e.g. struvite)

Risk Index §  include P, S, pH - related issues (not done)

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Results

addition of Mg

addition of carbon source

manipulation of internal recycle

flow rate

Preliminary results of the BSM2-P prototype (steady state)

0 20 40 60 80 100 1200

2

4

6

8

10

12

14

addition of Mg (kg day-1)(a)

scen

ario

1

g m

-3

TKNSNO3TN

0 20 40 60 80 100 1200

1

2

3

4

5

addition of Mg (kg day-1)(b)

g m

-3

TPSIP

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

2

4

6

8

10

12

14

addition of acetate (m3 day-1)(c)

scen

ario

2

g m

-3

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

1

2

3

4

5

addition of acetate (m3 day-1)(d)

g m

-3

0 1 2 3 4 5 60

2

4

6

8

10

12

14

internal recycle (Qintr/Qr)(e)

scen

ario

3

g m

-3

0 1 2 3 4 5 60

1

2

3

4

5

internal recycle (Qintr/Qr)(f)

g m

-3

0 20 40 60 80 100 1200

2

4

6

8

10

12

14


scen

ario

1

g m

-3

TKNSNO3TN

0 20 40 60 80 100 1200

1

2

3

4

5


g m

-3

TPSIP

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

2

4

6

8

10

12

14


scen

ario

2

g m

-3

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

1

2

3

4

5


g m

-3

0 1 2 3 4 5 60

2

4

6

8

10

12

14


scen

ario

3

g m

-3

0 1 2 3 4 5 60

1

2

3

4

5


g m

-3

0 20 40 60 80 100 1200

2

4

6

8

10

12

14


scen

ario

1

g m

-3

TKNSNO3TN

0 20 40 60 80 100 1200

1

2

3

4

5


g m

-3

TPSIP

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

2

4

6

8

10

12

14


scen

ario

2

g m

-3

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

1

2

3

4

5


g m

-3

0 1 2 3 4 5 60

2

4

6

8

10

12

14


scen

ario

3

g m

-3

0 1 2 3 4 5 60

1

2

3

4

5


g m

-3

0 20 40 60 80 100 1200

2

4

6

8

10

12

14


scen

ario

1

g m

-3

TKNSNO3TN

0 20 40 60 80 100 1200

1

2

3

4

5


g m

-3

TPSIP

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

2

4

6

8

10

12

14


scen

ario

2

g m

-3

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

1

2

3

4

5


g m

-3

0 1 2 3 4 5 60

2

4

6

8

10

12

14


scen

ario

3

g m

-3

0 1 2 3 4 5 60

1

2

3

4

5


g m

-3

0 20 40 60 80 100 1200

2

4

6

8

10

12

14


scen

ario

1

g m

-3

TKNSNO3TN

0 20 40 60 80 100 1200

1

2

3

4

5


g m

-3

TPSIP

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

2

4

6

8

10

12

14


scen

ario

2

g m

-3

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

1

2

3

4

5


g m

-3

0 1 2 3 4 5 60

2

4

6

8

10

12

14


scen

ario

3

g m

-3

0 1 2 3 4 5 60

1

2

3

4

5


g m

-3

0 20 40 60 80 100 1200

2

4

6

8

10

12

14


scen

ario

1

g m

-3

TKNSNO3TN

0 20 40 60 80 100 1200

1

2

3

4

5


g m

-3

TPSIP

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

2

4

6

8

10

12

14


scen

ario

2

g m

-3

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

1

2

3

4

5


g m

-3

0 1 2 3 4 5 60

2

4

6

8

10

12

14


scen

ario

3

g m

-3

0 1 2 3 4 5 60

1

2

3

4

5


g m

-3

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Discussion

Modelling requirements to realistically describe P

§  Compositional analysis §  Weak acid-base chemistry, pH estimation §  Numerical issues to solve (for PCM) §  Multiple mineral precipitation modelling

Development of control strategies to recover

N and P

§  Plant layout modifications §  Nutrient recovery processes §  Sulfur and iron interactions §  Agreement on evaluation criteria

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Conclusions Simultaneous C, N and P descriptions require substantial model (ASM, ADM and PCM) modifications/upgrades

Special attention must be placed on model interfacing, particularly regarding to ASM-ADM-ASM and both ASM-ADM with PCM

Plant-wide P removal requires definition of state variable empirical formulas plus elemental and COD and charge continuity checking

As far as overall P removal is concerned, metallic ions and pH in the AD play an important role

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Perspectives

§  BSM2-P free software available this year (Matlab) §  ADM1 model extended with ion pairing, speciation and

activities available for download §  Recovery processes should be added to plant layout

§  Processes related to sulfur need to be included

§  More collaboration between groups on plant-wide/system-wide model development needed

§  Integration of C, N, P, S, X, GHG, PCM, precipitation?

§  Towards BSM3 – catchment, sewer, plant, recipient

§  IWA Working Group a suitable platform for collaboration?

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Thank You for Your Attention!

Questions and comments?

(more BSM info at www.benchmarkwwtp.org) Financially supported by: EU projects PROTEUS (329349) and SANITAS (289193)

a benchmark simulation model to describe plant …a benchmark simulation model to describe...

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