The University of Queensland, Australia - … · 2015. 7. 22. · Model&based*selec,on*of*the*best*...

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Modelbased selec,on of the best viable opera,onal strategy for a full scale MBR Ignasi Rodriguez-Roda , Sara Gabarrón, Montse Dalmau, Hèctor Monclús, Julian Mamo, Jose Porro and Joaquim Comas 9th IWA Symposium on Systems Analysis and Integrated Assessment 1114 June 2015, Gold Coast, Australia

Transcript of The University of Queensland, Australia - … · 2015. 7. 22. · Model&based*selec,on*of*the*best*...

Page 1: The University of Queensland, Australia - … · 2015. 7. 22. · Model&based*selec,on*of*the*best* viableoperaonalstrategyfora full*scale*MBR! Ignasi Rodriguez-Roda, Sara Gabarrón,

Model-­‐based  selec,on  of  the  best  viable  opera,onal  strategy  for  a  

full  scale  MBR    Ignasi Rodriguez-Roda, Sara Gabarrón, Montse Dalmau,

Hèctor Monclús, Julian Mamo, Jose Porro and Joaquim Comas

9th  IWA  Symposium  on  Systems  Analysis  and  Integrated  Assessment  11-­‐14  June  2015,  Gold  Coast,  Australia

Page 2: The University of Queensland, Australia - … · 2015. 7. 22. · Model&based*selec,on*of*the*best* viableoperaonalstrategyfora full*scale*MBR! Ignasi Rodriguez-Roda, Sara Gabarrón,

MEMBRANES  FULL  SCALE  Area  (3  lines):  22.752  m2    

Cycles:    10’/30’’    

Flux:    27  LMH    

Design  flow:  90.000  m3/day    

IFAS  :  75.000  m3/day    

MBR  :    15.000  m3/day  

Pre-­‐treatment 1  mm  screening

Anoxictank 1

Anoxictank 2

Aerobictank 1

Aerobictank 2

Membranes  tank

Membranes  tank

Membranes  tank

Internal recirculation

Primary  Settler

BIOLOGICAL  TANK  – IFAS   Secondary  Settler

THE  PROCESS:  WWTP  Terrassa  (Catalonia)  

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MOTIVATION  

No  specific  process  problems…    No  interest  nor  budget..      

   Interest  from  academia:  LEQUiA-­‐UdG  and  ICRA  (Girona)    ExperMse  in  MBR  operaMon  and  in  process  opMmizaMon    1  on  going  PhD  in  MBR  opMmizaMon    Some  R+D  projects  to  cover  iniMal  expenses  

END  OF  THE  STORY  

Opportunity  (saving  cost..  Pay  back  soluMon…  no  environmental  risk)  

THERE  IS  A  POTENTIAL  STORY  

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METHODOLOGY  

1  PROCESS  CHARACTERIZATION    2  MODEL  CALIBRATION    3  EVALUATION  OF  ALTERNATIVES    4  NEGOTIATION  (DAM  and  ACA)    5  IMPLEMENTATION  AND  VALIDATION    

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PROCESS  CHARACTERIZATION  

Membrane  filtraMon  process  (TMP,  flux,  Permeability)  

Pre-­‐treatment 1  mm  screening

Anoxictank 1

Anoxictank 2

Aerobictank 1

Aerobictank 2

Membranes  tank

Membranes  tank

Membranes  tank

External recirculation

Internal recirculation

Primary  Settler

Influent  /  effluent  quality  (N,  C,  P)    

Sludge  quality  

Bioreactor  condiMons  (DO,  Redox,  Temperature,  …)    

Historical  data  (never  enough)  

3  days  experimental  campaign  

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METHODOLOGY  

1  PROCESS  CHARACTERIZATION    2  MODEL  CALIBRATION    3  EVALUATION  OF  ALTERNATIVES    4  NEGOTIATION  (DAM  and  ACA)    5  IMPLEMENTATION  AND  VALIDATION    

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MODEL  CALIBRATION  

Simulation platform:  WEST  (Mike  by DHI)

Caracterización  del  agua  de  entrada:  del  12/5/2013  12:00  al  15/5/13  12:00  (posterior  a  la  decantación)

Model layout:

V=  872.84m3

DO  =  0

V=  867.68m3DO  =  0

V=  1013m3DO  =  0.5

V=  1840m3DO  =  1.2

V=  248.25m3DO  =  5

Recirculación  del  tanque  de  membranas  al  tanque  aeróbico  =  4  Q

Recirculación  del  aeróbico  al  

anóxico:  4,5  Q

Waste flow:  160  m3/d

Biological  model:  ASM2d  

Membrane  behaviour:  resistance  –in  series  model  

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METHODOLOGY  

1  PROCESS  CHARACTERIZATION    2  MODEL  CALIBRATION    3  EVALUATION  OF  ALTERNATIVES    4  NEGOTIATION  (DAM  and  ACA)    5  IMPLEMENTATION  AND  VALIDATION    

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ROOM  FOR  OPTIMITZATION  

Reduce  energy  costs  

Improve  N  removal  efficiency  

EVALUATION  OF  ALTERNATIVES  

The  MBR  was  working  properly,  but…    

1  ReducMon  of  aerobic  tank  DO  2  ModificaMon  of  external/internal  recirculaMon  flow  rates  3  C  Source  addiMon  4  DO  control  of  external  recirculaMon   Effluent  quality  (EQI)        

Opera,onal  costs    (OC)      AeraMon  energy  (Nopens  et  al.,  2010;  Maere  et  al.,  2011)  

Pumping  energy  (Maere  et  al.,  2011)    Bulking  Risk  (Comas  et  al.,  2008)  

 BSM  Criteria  

NitrificaMon  was  achieved  before  the  membrane  tanks  Punctual  poor  denitrificaMon  

Scenario  analysis  (modelling)  

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DO: 1.2 DO: 1 DO: 0.8 DO: 0.5

Cos

ts (€·d

ay-1

)

40

50

60

70

80

90

100

EQ

(mg

pollu

tant·L

-1)

2500

2600

2700

2800

2900

3000

3100Costs EQ

0    

1    

2    

3    

4    

5    

6    

7    

8    

9    

Bulking  risk  (%

)  

Best  scenario  

1  Reduc,on  of  2nd  aerobic  tank  DO  set  point  

Scenarios  chosen  according  to  the  blowers  possibili,es  

EVALUATION  OF  ALTERNATIVES  (1)  

Page 11: The University of Queensland, Australia - … · 2015. 7. 22. · Model&based*selec,on*of*the*best* viableoperaonalstrategyfora full*scale*MBR! Ignasi Rodriguez-Roda, Sara Gabarrón,

Cos

ts (€·d

ay-1

)

40

50

60

70

80

90

100

Effl

uent

qua

lity

(mg

pollu

tant·L

-1)

2500

3000

3500

4000Internal Recirculation:

4.5 QInternal Recirculation:

6 QInternal Recirculation:

2 QInternal Recirculation:

1 Q

PE EQI

External recirculation (Q)

PE Real operational conditions

6Q 6Q 6Q 6Q4Q 4Q4Q 4Q2Q 2Q 2Q 2Q1Q 1Q 1Q 1Q

NO3-­‐:

8,76  mg·∙L-­‐1

NO3-­‐:  

18,07  mg·∙L-­‐1

2  Modifica,on  of  the  external  and  internal  recycle  flow  rate  

EVALUATION  OF  ALTERNATIVES  (2)  

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0:00 12:00 0:00 12:00 0:00 12:00 0:00 12:00 0:00

NO

3- -N (m

g·L-1

)

0

5

10

15

20

Hours

Simulated DO:0.8 mg/L

A  NO3-­‐-­‐N  effluent  

concentra,on  reduc,on  of  30%  

0:00 12:00 0:00 12:00 0:00 12:00 0:00 12:00 0:00

NO

3- -N (m

g·L-1

)

0

5

10

15

20

DO: 0.8 mg·L-1 and Dynamic methanol addition

Hours

Simulated DO:0.8 mg/L

Cost  analysis  predicted  an    increment  of  41  %  of  the  total  costs    (aeraMon  and  pumping  energy  costs)    

EVALUATION  OF  ALTERNATIVES  (3)  

3  C  source  addi,on  

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DO  >  2  mg/L  DO  <  2  mg/L  To  the  AEROBIC  TANK  To  the  ANOXIC  TANK  

Pre-­‐treatment 1  mm  screening

Anoxictank 1

Anoxictank 2

Aerobictank 1

Aerobictank 2

Membranes  tank

Membranes  tank

Membranes  tank

External recirculation

Internal recirculation

Primary  Settler

DO  sensor  

ANOXIC   AEROBIC   MEMBRANES  

DO  concentra,on  ≈  5  ppm    (Tan  et  al.,  2008)  

EVALUATION  OF  ALTERNATIVES  (4)  

4  Control  of  the  external  Sludge  recircula,on  DO  

Page 14: The University of Queensland, Australia - … · 2015. 7. 22. · Model&based*selec,on*of*the*best* viableoperaonalstrategyfora full*scale*MBR! Ignasi Rodriguez-Roda, Sara Gabarrón,

METHODOLOGY  

1  PROCESS  CHARACTERIZATION    2  MODEL  CALIBRATION    3  EVALUATION  OF  ALTERNATIVES    4  NEGOTIATION  (DAM  and  ACA)    5  IMPLEMENTATION  AND  VALIDATION    

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IMPLEMENTATION  AND  VALIDATION  

Characteriza,on  

Membrane  filtraMon  process    (TMP,  flux,  Permeability)  Influent  /  effluent  quality  

Sludge  quality  

Bioreactor  condiMons    (DO,  Redox,  Temperature,  …)    

10:00 22:00 10:00 22:00 10:00 22:00 10:00 22:00

N-N

O3-

(mg·

L-1)

0

10

20

30

401st Experimental campaign DO: 1.2 mg/L 2nd Experimental campaign DO:0.8 mg/LAfter implementation of DO: 0,8 mg/L

Effluent    

1  Reduc,on  of  DO  set  point  to  0.8  mg/L  in  the  second  aerobic  reactor  2  Maintain  int/ext  rec  flow  rates  3   DO   control   system   for   the   external   recircula,on   in   order   to   ensure   the   anoxic  condi,ons  in  the  anoxic  tank  4  Monitor  results!!  

Page 16: The University of Queensland, Australia - … · 2015. 7. 22. · Model&based*selec,on*of*the*best* viableoperaonalstrategyfora full*scale*MBR! Ignasi Rodriguez-Roda, Sara Gabarrón,

CONCLUSIONS  

More  interes,ng  for  academia  than  for  the  companies    

→  Improved  the  Nitrogen  removal  efficiency  (27  %)  

→  Reduced  the  biological  aera,on  costs  (7  %)  

→  Shown   the   efficiency   of   the   DO   control   system   for   the   external  recircula,on  in  order  to  ensure  the  anoxic  condi,ons  in  the  anoxic  tank  

The  op,miza,on  strategies  implemented  in  the  full-­‐scale  MBR  have….    

Model  based  approach  MBR  (N/D,  but  filtra,on  is  s,ll  an  issue…  rela,onship  with  biology)  

 Op,mal  vs.  viable  (implementa,on  vs  publica,on)  

Indirect  R+D  funding..  Competence  to  consul,ng  companies?    

Page 17: The University of Queensland, Australia - … · 2015. 7. 22. · Model&based*selec,on*of*the*best* viableoperaonalstrategyfora full*scale*MBR! Ignasi Rodriguez-Roda, Sara Gabarrón,

9th  IWA  Symposium  on  Systems  Analysis  and  Integrated  Assessment  11-­‐14  June  2015,  Gold  Coast,  Australia

THANK  YOU  VERY  MUCH