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a platform supporting residential water
management through smart meters
and data intensive modeling
Andrea Cominola, Rohan Nanda, Matteo Giuliani,
Dario Piga, Andrea Castelletti, Andrea Emilio Rizzoli,
Alexandros Maziotis, Paola Garrone and Julien J. Harou
RESIDENTIAL WATER MANAGEMENT
URBAN CONTEXT
RESIDENTIAL WATER MANAGEMENT
URBAN CONTEXT
2014 2030 2050
66%
54%
urban
population
growth
Source: United Nations. Department of Economic and Social Affairs. Population Division, 2010
RESIDENTIAL WATER MANAGEMENT
URBAN CONTEXT
2014 2030 2050
66%
54%
urban
population
growth
41 megacities
worldwide
Source: United Nations. Department of Economic and Social Affairs. Population Division, 2010
AN EXAMPLE: LONDON
UK_WATER SUPPLY UTILITY
15 million customers
2.6 Gl/day drinking water
3 billion $ revenue (2013-14)
HOW TO FILL THE GAP?
UK_WATER SUPPLY UTILITY
15 million customers
2.6 Gl/day drinking water
3 billion $ revenue (2013-14)
water demand
available resource
2010 2040
HOW TO FILL THE GAP?
UK_WATER SUPPLY UTILITY
15 million customers
2.6 Gl/day drinking water
3 billion $ revenue (2013-14)
water demand
CAPACITY EXPANSION
2010 2040
HOW TO FILL THE GAP?
UK_WATER SUPPLY UTILITY
15 million customers
2.6 Gl/day drinking water
3 billion $ revenue (2013-14)
DEMAND MANAGEMENT
CAPACITY EXPANSION
2010 2040
THE PROJECT
high resolution water
consumption data
interaction with customers
for socio-psychographic
data gathering
management strategies:
dynamic pricing
rewards
INNOVATIVE WATER
DEMAND MANAGEMENT
THE PLATFORM
HIGH RESOLUTION WATER CONSUMPTION DATA
smart meters
and end use
analysis
CUSTOMERS’ SOCIO-PSYCHOGRAPHIC ATTRIBUTES
smart meters
and end use
analysis
gamified bill
online and
board game
CUSTOMERS’ BEHAVIOR MODELING
smart meters
and end use
analysis
behavioral modeling
water
consumption
drivers
identification
water
consumption
level forecast at
the customer
scale gamified bill
online and
board game
MANAGEMENT AND CONTROL
smart meters
and end use
analysis
gamified bill
online and
board game
behavioral modeling
water
consumption
drivers
identification
water
consumption
level forecast at
the customer
scale
administrator
dashboard
dynamic water pricing
tailored feedbacks
prescriptive norms
gamified bill
Response to
WDMS
What is there behind the platform?
Some technological insights
MANAGEMENT AND CONTROL
administrator
dashboard
gamified bill
online and
board game
behavioral modeling
water
consumption
drivers
identification
water
consumption
level forecast at
the customer
scale
dynamic water pricing
tailored feedbacks
prescriptive norms
gamified bill
Response to
WDMS
smart meters
and end use
analysis
WATER CONSUMPTION DISAGGREGATION INTO END USES
Toilet
Shower
Dishwasher
Washing machine
Garden
Swimming pool
ONE MEASURE MANY END USES
Need for fully automated
disaggregation algorithms
overlapping,
simultaneous water
end uses
human-dependent
vs
automatic fixtures
Source: Nguyen et al., 2013
A NEW END USE CHARACTERIZATION ALGORITHM
MODEL FEATURES
Factorial Hidden Markov Model
Iterative Subsequence Dynamic Time Warping
MODEL PERFORMANCE
ABLE TO CHARACTERIZE UP TO 4-5 SIMULTANEOUSLY WORKING FIXTURES
Source: Batra et al., 2014, Muller, 2007, Gharahmani, 1997
A NEW END USE CHARACTERIZATION ALGORITHM
ACCURACY
ON EVENT
DETECTION
ACCURACY
ON
TRAJECTORIES
Finally, how can the platform support
the management of the resource?
THE PLATFORM: SUPPORTING THE MANAGEMENT
city scale
strategic level
planning
THE PLATFORM: SUPPORTING THE MANAGEMENT
city scale user level
customized management
tailored WDMS
strategic level
planning
THE PLATFORM: SUPPORTING THE MANAGEMENT
city scale user level
customized management
tailored WDMS
strategic level
planning
consortium cluster
thank you
http://www.smarth2o-fp7.eu/
@smartH2Oproject
#SmartH2O
Andrea Cominola
andrea.cominola@polimi.it
Politecnico di Milano
Department of Electronics,
Information and Bioengineering

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The SmartH2O project: a platform supporting residential water management through smart meters and data intensive modeling

  • 1. a platform supporting residential water management through smart meters and data intensive modeling Andrea Cominola, Rohan Nanda, Matteo Giuliani, Dario Piga, Andrea Castelletti, Andrea Emilio Rizzoli, Alexandros Maziotis, Paola Garrone and Julien J. Harou
  • 3. RESIDENTIAL WATER MANAGEMENT URBAN CONTEXT 2014 2030 2050 66% 54% urban population growth Source: United Nations. Department of Economic and Social Affairs. Population Division, 2010
  • 4. RESIDENTIAL WATER MANAGEMENT URBAN CONTEXT 2014 2030 2050 66% 54% urban population growth 41 megacities worldwide Source: United Nations. Department of Economic and Social Affairs. Population Division, 2010
  • 5. AN EXAMPLE: LONDON UK_WATER SUPPLY UTILITY 15 million customers 2.6 Gl/day drinking water 3 billion $ revenue (2013-14)
  • 6. HOW TO FILL THE GAP? UK_WATER SUPPLY UTILITY 15 million customers 2.6 Gl/day drinking water 3 billion $ revenue (2013-14) water demand available resource 2010 2040
  • 7. HOW TO FILL THE GAP? UK_WATER SUPPLY UTILITY 15 million customers 2.6 Gl/day drinking water 3 billion $ revenue (2013-14) water demand CAPACITY EXPANSION 2010 2040
  • 8. HOW TO FILL THE GAP? UK_WATER SUPPLY UTILITY 15 million customers 2.6 Gl/day drinking water 3 billion $ revenue (2013-14) DEMAND MANAGEMENT CAPACITY EXPANSION 2010 2040
  • 9. THE PROJECT high resolution water consumption data interaction with customers for socio-psychographic data gathering management strategies: dynamic pricing rewards INNOVATIVE WATER DEMAND MANAGEMENT
  • 11. HIGH RESOLUTION WATER CONSUMPTION DATA smart meters and end use analysis
  • 12. CUSTOMERS’ SOCIO-PSYCHOGRAPHIC ATTRIBUTES smart meters and end use analysis gamified bill online and board game
  • 13. CUSTOMERS’ BEHAVIOR MODELING smart meters and end use analysis behavioral modeling water consumption drivers identification water consumption level forecast at the customer scale gamified bill online and board game
  • 14. MANAGEMENT AND CONTROL smart meters and end use analysis gamified bill online and board game behavioral modeling water consumption drivers identification water consumption level forecast at the customer scale administrator dashboard dynamic water pricing tailored feedbacks prescriptive norms gamified bill Response to WDMS
  • 15. What is there behind the platform? Some technological insights
  • 16. MANAGEMENT AND CONTROL administrator dashboard gamified bill online and board game behavioral modeling water consumption drivers identification water consumption level forecast at the customer scale dynamic water pricing tailored feedbacks prescriptive norms gamified bill Response to WDMS smart meters and end use analysis
  • 17. WATER CONSUMPTION DISAGGREGATION INTO END USES Toilet Shower Dishwasher Washing machine Garden Swimming pool ONE MEASURE MANY END USES Need for fully automated disaggregation algorithms overlapping, simultaneous water end uses human-dependent vs automatic fixtures Source: Nguyen et al., 2013
  • 18. A NEW END USE CHARACTERIZATION ALGORITHM MODEL FEATURES Factorial Hidden Markov Model Iterative Subsequence Dynamic Time Warping MODEL PERFORMANCE ABLE TO CHARACTERIZE UP TO 4-5 SIMULTANEOUSLY WORKING FIXTURES Source: Batra et al., 2014, Muller, 2007, Gharahmani, 1997
  • 19. A NEW END USE CHARACTERIZATION ALGORITHM ACCURACY ON EVENT DETECTION ACCURACY ON TRAJECTORIES
  • 20. Finally, how can the platform support the management of the resource?
  • 21. THE PLATFORM: SUPPORTING THE MANAGEMENT city scale strategic level planning
  • 22. THE PLATFORM: SUPPORTING THE MANAGEMENT city scale user level customized management tailored WDMS strategic level planning
  • 23. THE PLATFORM: SUPPORTING THE MANAGEMENT city scale user level customized management tailored WDMS strategic level planning