Intelligent membrane management to enhance resource ...
Transcript of Intelligent membrane management to enhance resource ...
Intelligent membrane management to enhance resource recovery opportunities Sandeep Sathyamoorthy IWA Aspire 2019, Hong Kong November 1, 2019
IOT & AI now commonly impact & benefit our daily lives
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And is coming to a WRRF screen near you
Figure courtesy of Atonix Digital
Framework for today’s talk
Opportunities Solutions & Strategies
The Fine Print…
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Opportunities to maximize the value of analytics, machine learning and connected analyses
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0% 20% 40% 60%
PerformanceMonitoring
AssetManagement
TreatmentOptimization
2018 Strategic Directions: Black & Veatch Water Industry Report and Survey
Operational areas where data analytics and
automated monitoring will help improve
your organization?
Energy costs of membrane management in water reuse schemes
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Non-potable Reuse Potable Reuse
Influent Pumping
5% Headworks1%
Biological Process
26%
MBR Management
39%
Disinfection10%
Odour Control15%
Misc.4%
Pumping6%
Headworks2% Biological
Process9%
MBR Management
13%
RO Management
41%
Advanced Oxidation
22%
Odour Control7%
Misc.0%
5% reduction in MBR management costs can result in 1-2% OPEX reduction
5% reduction in MBR & RO management costs can result in 2-3% OPEX reduction
Membrane replacement costs are directly influenced by operation and water quality
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Water Quality (DOC, TOC,
MLSS, NHX-N,…)
Filterability &
Flux Decline
Short & long term
membrane performance
Membrane OPEX &
Replacement Costs
Membrane Operation
(flux, initial flux) Enhanced operation to increase membrane life results in 2%-5% reduction in 20-yr present worth
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Years in Operation
Operational modifications to decrease membrane replacement frequency
Process Risk Management & Treatment Performance Optimization
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Virus Giardia Cryptosporidium Regulatory Requirement
12 10 10
BNR-MBR RO UV-AOP Free-Cl2 Underground Retention
UF RO UV-AOP Free-Cl2 Underground Retention BNR
Process Risk Management & Treatment Process Optimization in Potable Reuse
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Biological Treatment AWPF Supply Water Feed System
DPR Supply Water
Manage the quality/quantity of this (intermediate) raw material Other Uses
Critical Control Point
RAS
WAS
UF Membrane
Solutions & Strategies – Some Examples
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Solutions and Strategies
Figures courtesy of Atonix Digital
Actively managing membrane energy requirements
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In an MBR - energy costs driven by air scour
Current Approach(es) to MBR Air Scour
Continuous aeration (with high/low SPs)
Intermittent aeration (with high/low SPs)
=> Two basic control variables: Air Flow Time
• Results in (sometimes) OVER-scour & (sometimes) UNDER-scour
• Membrane fouling is a complex, multidimensional process impacted by a range of variables
• Need a scour tool capable of understanding, then managing scour based on fouling needs
Using machine learning & analytics tools for air-scour management
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SRT
F/M
NHx-N
Flux
TMP, Permeability w/ history
Scour History
MLSS
Parameter X,Y,Z
.....
Neural Network Kohonen Bayesian
Deep Machine Learning & Scour Manager
Delphi knowledge (e.g., manual intervention - scour now)
Fouling model(s) Theoretical framework
Intelligent Adaptive MBR Scour Management System
Managing supply water quality in potable reuse
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Measure Turbidity
No Action Required
Divert Supply Water Away from AWPF
Alarms Inform shift supervisors Initiate mitigation measures
Wait YY min
Alert Level Turbidity >
N
Y
Max. Level Turbidity >
N
Y
Inform Corrective Action Team shift supervisor, Sep’n process SME, AWPF lead operator, AWPF process SME
Initiate False Positive Verification
Automated Actions • Instrument self
verification Human Actions • Sampling system • Visual inspection
Wait XX min
Operational Verification & Recommended Actions
Operator System Reset
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0 5 10 15 20Seco
ndar
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luen
t Tur
bidi
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(NTU
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Secondary Effluent TSS (mg/L)
Using water’s fingerprint to manage attention points
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0
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Sec.
Eff.
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TU)
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Eff.
TSS
(mg/
L) S.E. SS S.E. Ntu
Turbidity/TSS
Fluorescence Spectrum
Early Warning Actions
KPIs
Attention Point Health
DECISION SUPPORT SYSTEM
• Big Data Analytics • Machine Learning
Using water’s fingerprint to manage attention points
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Eff.
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TSS
(mg/
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Turbidity/TSS
Fluorescence Spectrum
Early Warning Actions
KPIs
Attention Point Health
DECISION SUPPORT SYSTEM
• Big Data Analytics • Machine Learning
Figure courtesy of Atonix Digital
The Fine Print
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things you need to really, really pay attention to if you want the system to actually work….
Xxxxx xxxx
Managing the data highway
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What do you really want to
measure?
How much data is needed?
Accuracy of the data?
What do you want do with data?
Who needs the information?
• TSS vs. Turbidity • Ammonia-N in Oxic zone vs.
Supply Water Ammonia-N?
• Frequency
• Granularity – e.g., total particle counts vs. bins
• mg/L (ppm) vs. ug/L (ppb)
• Monitoring • Control • Reporting
Using the right tools for the job, in the right way
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24-h Diurnal
2nd AE Zone 3rd AE Zone
Optimal Probe Range
Amm
onia
-N C
onc.
1st AE Zone
Ammonia-N concentration may be one of many predictor variables in a multivariate feature extraction algorithm or input to a neural net
Tools need to well looked after – enhancing the vernacular to include validation and data quality management
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Process Function
Instrument Type Cleaning Validation Calibration Maintenance
Ammonia-N, Nitrate-N
Ion Selective Electrode (ISE)
1-2 times per week
2-3 times per week
1-2 times every 2 weeks
1-2 times per month
Dissolved Oxygen
optical (e.g., LDO)
1-2 times per week
2-3 times per week
1-2 times every 2 weeks
1-2 times per month
Turbidity Optical or Laser 2-3 times per week
1-2 times every 2 weeks
1-2 times per month
1-2 times per month
pH/ORP ISE 1-2 times per week
1-2 times per week
1-2 times per month
1-2 times per month
Managing instrument risks through self diagnostic tools
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Key Take Aways
• IIOT/AI etc. is here – we need to “acclimate” and find the best applications
• Using AI is not likely to reduce the need for skilled operations professionals – BUT it will require new, enhanced skill sets
• GIGO – manage, maintain and validate instruments
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Sandeep Sathyamoorthy +1.925.949.5913 [email protected]