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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 [email protected]
Politecnico di Milano
Department of Electronics, Information and Bioengineering
