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selecting the optimal WWTP confjguration including resource - - PowerPoint PPT Presentation

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selecting the optimal WWTP confjguration including resource recovery units ivko Juni-Zonta*, Albert Guisasola, Juan Antonio Baeza GENOCOV. Department of Chemical, Biological and Environmental Engineering, Universitat Autnoma de

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selecting the optimal WWTP confjguration including resource recovery units

Živko Južnič-Zonta*, Albert Guisasola, Juan Antonio Baeza

  • GENOCOV. Department of Chemical, Biological and Environmental Engineering,

Universitat Autònoma de Barcelona, Catalonia, Spain 7th International Conference on Sustainable Solid Waste Management – 26th June 2019

HERAKLION2019-SSWM *Presenting author

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Scale-up of low-carbon footprint MAterial Recovery Techniques for upgrading existing WWTP

HERAKLION2019-SSWM 2

Funded by the Horizon 2020 Framework Programme of the European Union under grant agreement No 690323

DSS for selecting the optimal WWTP confjguration including resource recovery units

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MAIN GOAL

REDUCE energy and environmental footprint RECOVER valuable materials (water, cellulose, biopolymers, nutrients) PRODUCE products exploitable in construction, chemical and agriculture

HERAKLION2019-SSWM 3 DSS for selecting the optimal WWTP confjguration including resource recovery units

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Scale-up of low-carbon footprint MAterial Recovery Techniques for upgrading existing WWTP

HERAKLION2019-SSWM 4

Started Juny 2016 Ends in Juny 2020

DSS for selecting the optimal WWTP confjguration including resource recovery units

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Scale-up of low-carbon footprint MAterial Recovery Techniques for upgrading existing WWTP

HERAKLION2019-SSWM 5

Total EC funding

7,5M€

DSS for selecting the optimal WWTP confjguration including resource recovery units

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Scale-up of low-carbon footprint MAterial Recovery Techniques for upgrading existing WWTP

HERAKLION2019-SSWM 6

Partners

26

DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 7

SMARTech pilot-plants

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DSS for selecting the optimal WWTP confjguration including resource recovery units

DSS objective

Advise the potential stakeholders

  • n how to implement the SMART
  • Plant Technologies for their specifjc

wastewater treatment problem

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HERAKLION2019-SSWM 8 DSS for selecting the optimal WWTP confjguration including resource recovery units

SMARTech process models

  • Complex dynamics (ASM2d,

ADM1)

  • Discrete events (SBR)
  • Complex control systems
  • Large system of difgerential-

algebraic equations (DAE) Energy Cellulose Biopolym ers Nutrients

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HERAKLION2019-SSWM 9

Dynamic fjne-screen and post- processing of cellulosic sludge (ST1)

DSS for selecting the optimal WWTP confjguration including resource recovery units

Energy Cellulose Biopolym ers Nutrients

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HERAKLION2019-SSWM 10

Polyurethane-based anaerobic digestion bio-fjlter (ST2a)

DSS for selecting the optimal WWTP confjguration including resource recovery units

Energy Cellulose Biopolym ers Nutrients

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HERAKLION2019-SSWM 11

Short-Cut Enhanced Phosphorus and PHA Recovery (SCEPPHAR) main-stream process (ST2b)

DSS for selecting the optimal WWTP confjguration including resource recovery units

Energy Cellulose Biopolym ers Nutrients

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HERAKLION2019-SSWM 12

Tertiary hybrid ion exchange for N and P nutrients recovery (ST3)

DSS for selecting the optimal WWTP confjguration including resource recovery units

Energy Cellulose Biopolym ers Nutrients

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HERAKLION2019-SSWM 13

Short-Cut Enhanced Nutrient Abatement (SCENA) and

  • rdinary digestion side-stream

process (ST4a)

DSS for selecting the optimal WWTP confjguration including resource recovery units

Energy Cellulose Biopolym ers Nutrients

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HERAKLION2019-SSWM 14

SCENA and CAMBI-enhanced digestion side-stream process (ST4b)

DSS for selecting the optimal WWTP confjguration including resource recovery units

Energy Cellulose Biopolym ers Nutrients

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HERAKLION2019-SSWM 15

SCEPPHAR side-stream process (ST5)

DSS for selecting the optimal WWTP confjguration including resource recovery units

Energy Cellulose Biopolym ers Nutrients

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Which plant confjguration is best for me? Try our hyper-tech solution Decision Support System!

HERAKLION2019-SSWM 16 DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 17

STEP1: Design problem set-up

  • New design or retrofjt

DSS for selecting the optimal WWTP confjguration including resource recovery units

  • Geo-location (weather)
  • PE, legal limits, etc.
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HERAKLION2019-SSWM 18

STEP2: Wastewater infmow generation

  • Dry weather model
  • Wet weather model
  • Sewer model

Mayor rain event Week Weekend Infjltration

DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 19

STEP3: Superstructure generation and simulation Pre-treatment Activated Sludge Digestion

DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 20

STEP3: Superstructure generation and simulation

  • Conventional A2O process
  • Redeclare Stage3 with ST2b
  • Automatic built-up of WWTP confjgurations!

DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 21

STEP4: Objective values estimation

  • Effmuent Quality Index (EQI)
  • Frequency Effmuent Violations (FEV)
  • Net Present Value (NPV)
  • GreenHouse Gas (GHG) emissions

Compute for all possible WWTP design confjgs!

DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 22

STEP5: Design confjguration sorting Multi Criteria Decision Making (MCDM) based on user preferences Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)

DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 23

STEP6: Design parameter optimization Minimize NPV optimizing Volume, S/L separation capacity, etc. Constraints on FEV, HRT, SOR, etc. Decrease confjgurations to optimize with MCDM

DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 24

STEP7: Uncertainty analysis Input and parameter uncertainty Sensitivity analysis given the optimal design

DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 25

Conclusions

  • Design is based on dynamic and static process models
  • Effmuent limits fully accounted
  • Design of discrete event processes (e.g. SBR)
  • Design integrates the WWTP control system
  • Infmuent model for Europe

For future work

  • Test global optimization strategies for design optimization
  • Build user friendly web-interface
  • Perform simulations in a distributed computing environment
  • Integrate other resource recovery technologies
  • Increase the range of application of the infmow model to North

America

  • Integrate Life Cycle Analysis frameworks

DSS for selecting the optimal WWTP confjguration including resource recovery units

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HERAKLION2019-SSWM 26

Questions?

DSS for selecting the optimal WWTP confjguration including resource recovery units

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selecting the optimal WWTP confjguration including resource recovery units

Živko Južnič-Zonta*, Albert Guisasola, Juan Antonio Baeza

  • GENOCOV. Department of Chemical, Biological and Environmental Engineering,

Universitat Autònoma de Barcelona, Catalonia, Spain 7th International Conference on Sustainable Solid Waste Management – 26th June 2019

HERAKLION2019-SSWM *Presenting author