The document discusses control and optimization of wastewater treatment plants through monitoring and data analysis. It describes using measurements from various sensors and analyzing the data to create intelligent indicators and traffic light systems to monitor plant performance and detect faults. The data is also used for decision support, modeling subprocesses, and integrating process control and automation. The goal is to improve efficiency, performance, and environmental impact through real-time monitoring and optimization of wastewater treatment operations.

1. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Control and optimization of wastewater
treatment plants
Esko Juuso
Control Engineering Group, Faculty of Technology
University of Oulu, Finland

2. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Measurements à Applications
• Basis: Measurements
– Microwave, image processing, LED, ...
– Sampling, dilution, cleaning, uncertainty
– Towards on-line and process
• Methodology: Data analysis à pipelined
• Intelligent analysers (soft sensors)
• Decision support & operating conditions
• Modelling with specific submodels
• Integration to automation
• Risk analysis
• Services

3. MMEA Wastewater Keydemo
Helsinki 17 September 2015
WP 2 State model
• Trafic lights
• Environmental efficiency
• Calculation methods
WP 4 Measurements
• Image processing
• Biodegradability
• Contamination
WP 1 MMEA Platform
• Data sources
• Data processing chain
• Quality Control
• Anomaly detection
WP 2 Environmental
Efficiency
• Real-time indicators
• Life cycle analysis
How industrial applications
can utilize MMEA platform
and vice versa?
How efficiency (energy, material, environment)
and performance of an industrial system can be
improved by monitoring and diagnosis applications?

4. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Monitoring and control
• Data analysis: nonlinear scaling à indices, limits
• Intelligent indicators
– Scaled values [-2, 2]
– Trend indices
• Plant performance: long windows
• Control + DSS: short windows
• Traffic lights
– Levels &Trends
• Cases: wastewater treatment (WWT) plants
– Pulp mill WWT (Stora Enso, Oulu)
– Municipal WWT (HSY),
• Automation systems à Online (Valmet)

5. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Measurements à Control
• Data analysis
– Limits
• Trend analysis
– Changes
– Trajectories
• Uncertainty
Detection of operating conditions
- system adaptation
- fault diagnosis, maintenance,
- performance, quality
Dynamic simulation
- controller design, prediction
Intelligent analysers
- sensor fusion
- software sensors
- trends
Intelligent control
- adaptation
- model-based
Measurements
- on-line analysers
- DSP
Intelligent actuators
- model-based
Intelligent analyser
(Software sensor)
Controller
Stricter requirements
Capacity increase
Fluctuations
Intelligent + MPC

6. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Signal processing
- Derivation
- Integration, etc.
Feature extraction
- Norms
- Histograms
Interpolation
Nonlinear scaling
LE models
Fuzzy rules
Signals
Process measurements
Process measurements
Laboratory analysis
Intelligent indices
Trend indices
Process states
• Process Cases & Faults
• Quality, Efficiency, …
Measurements à Features à Indices
Sensor selection
Feature selection
Each measurement
analysed separately

7. MMEA Wastewater Keydemo
Helsinki 17 September 2015
• A generalised norm
• Special cases. Min ... Max
– Arithmetic mean
– Standard deviation, rms value
• Variable specific
Data analysis: generalised norms
p is a real numberSeparately for each variable x j

8. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Generalised moments à Limits
• Normalised moments
• Skewness
– Positive
– Symmetric
– Negative
• Generalised moment
k = 3 Skewness
k = 4 Kurtosis( )[ ]
k
X
k
k
XEXE
s
g
)(-
=
03 >g
03 <g
03 =g
( )
k
X
k
p
p
k
MXE
s
g
a
ta
úû
ù
êë
é -
=
)(
Central value

9. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Nonlinear scaling
Measurements
Meanings
Expert
knowledge
- Linguistic levels can translated into numbers
- Natural language

10. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Shortage of nutrients
Too much nutrients
High oxygen
Low oxygen
High temperature
Low temperature
High flow
Low flow
Very good
Low reduction
Settling problems
Very good
Warnings
Process states & Limits Traffic lights

11. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Trend analysis
åå -=-= +
-
+
=
k
nki
j
L
k
nki
j
S
T
j
LS
kX
n
kX
n
kI )(
1
1
)(
1
1
)(
Change of trend index
Trend index

12. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Treatment results
Low
reduction
Settling
problems
Very good
Very good

13. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Decision support systems
• DSS system
architecture
• Data visualization
– Traffic lights
– Trends
• Diagnosis tools
– Variable specific
– Combined
• Modelling
• “What if” simulations
• Detected problems
• Advisory tools for
operator support
à Process control
• Connectivity of
industrial information
systems with MMEA
platform

14. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Intelligent analyser
(Software sensor)
Control
Decision making
Intelligent analyser
(Software sensor)
Intelligent analyser
(Software sensor)
Control
Decision making
Control
Decision making
Performance
analysis
Adaptation
Expertise
Optimisation
Measurement
technology
Monitoring à Decision support
• Quality
• Uncertainty handling
• Online analysers and laboratory measurements
• Open data (weather)

15. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Submodels
Water treatment
Fuzzy LE blocks
BioMass
Load
- Load
- Nutrients
- Oxygen
- Temperature
Condition of
the biomass

16. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Measurements à Automation
à Risk Management
Measurements
Intelligent
analysers
Risk
Management
Environment
Weather
Hydrological forecasts
Processes

17. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Risk management
Control
Decision making
Control
Decision making
Process control
Decision making
Modelling
Risk identification
Risk analysis
High-level control
Diagnostics
Performance analysis
Enviromental measurementsAdaptation
Intelligent analyser
(Software sensor)
Intelligent analyser
(Software sensor)
Intelligent analyser
(Software sensor)
Measurement
technology
Process
Measurements
Modelling
Open data
Process insight, weather, water balance
Intelligent analysers: traffic lights, trends
New measurements
New measurements
Forecasting
Global
markets
Situation awareness

18. MMEA Wastewater Keydemo
Helsinki 17 September 2015
WP3 Remote Sensing
- Radar
- Lidar
- Airborne
WP4
- Solution studies
- High performance
• on-line monitoring
WP1 Data Management
- Data Sources
- Processing
- Testbed
WP2 EE Management/
- Monitoring methods
- Decision Support
- Application cases
EE Services
Concepts
WP2
Fouling and contamination of sensors
Wastewater measurements
Weather observations & forecasting
Quality control & anomaly detections
Data operator & data sources
Value chain for environmental
management
Monitoring methods and tools
Monitoring and management framework
Decision support systems
Low-cost sensors in water analytics
Atmospheric boundary layer sensing
with radar, lidar & airborne
Instruments
Probabilistic nowcasting

19. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Smart Applications in Industrial Internet
Thing
Thing
Thing
Act!
Store,
analyse,
refine,
etc.
Local integrated applications!
Utilise!
Local processing
à Efficient local use
à Less data transfer
Things
Services
Control
Decision making
Control
Decision making
Process control
Decision making
Modelling
Risk identification
Risk analysis
High-level control
Diagnostics
Performance analysis
Enviromental measurementsAdaptation
Intelligent analyser
(Software sensor)
Intelligent analyser
(Software sensor)
Intelligent analyser
(Software sensor)
Measurement
technology
Process
Measurements
Modelling
Open data
GSPC & Trends
I2oSIoT
Experts

20. MMEA Wastewater Keydemo
Helsinki 17 September 2015
Conclusions
• Process measurements à real-time
• Sampling à Laboratory analysis
• More real-time measurements
• Combine measurements + trend analysis + GSPC
• Monitoring à Control & Optimization
• Forecasting + Risk identification
• Situation awareness
• Services
Environment
WWTP
Active sludge
Open data
Participatory
observations