This document discusses using smart water meter data and analytics to improve demand management and customer relationships for water utilities. It describes collecting high frequency consumption data from smart meters, analyzing the data to classify customers and detect usage patterns, and developing a consumer portal with personalized tips, goals, comparisons to peers, and games to motivate more efficient water use. The system is currently being piloted with 400 households in Switzerland and will be deployed in London and Valencia in future years.

1. From Smart Water Meters to Demand and Customer
Relationship Management
Turning smart water meter data into a business intelligence tool
Piero Fraternali Giorgia Baroffio Andrea Cominola
Politecnico di Milano
piero.fraternali | giorgia.baroffio@polimi.it andrea.cominola@polimi.it

2. OUR COMMON PROBLEM: THE EXAMPLE OF: LONDON
2
UK_WATER SUPPLY UTILITY
15 million customers
2.6 Gl/day drinking water
3 billion $ revenue (2013-14)

3. Demand management
DEMAND MANAGEMENT
CAPACITY EXPANSION
2010 2040

4. consortium cluster

5. From water data to customer relationship and
demand management
5
Data acquisition
and consolidation
Consumption data
repository
• Privacy
• Security
Consumer Portal
• Awareness
• Feedback Engagement & Behavior Change
• Recommendations
• Goals, Achievements, Rewards
Water data analytics
• End use disaggregation
• Consumption patterns detection
User modeling
• Clustering
• Demand prediction and simulation
Personalized tips
Household features

6. Engagement: motivation drivers
6
extrinsic
intrinsic
Price discounts
Redeemable goods
Consumption Goals
Water games
Educational
resources
Social sharing
Peer comparison
Water diaryAwareness
tools

7. Awareness
7

8. Peer comparison
8

9. Water education
9

10. Water games

11. Redeemable goods
11

12. Data analytics
12
Outalgorithm

13. User modeling
13
Users’ BEHAVIORAL MODELING through
CLUSTERING and CLASSIFICATION techniques.
11 %
52 %
37 %
High consumers
Medium consumers
Low consumers
Hour the day
0 5 10 15 20 25
Normalizedhouseholdconsumption
0
0.05
0.1
0.15
WATER CONSUMPTION PROFILES

14. Status
• Today
– Gamified Consumer Portal in alpha test
– 400 households in Canton Ticino (CH), AMI at 1 hr resolution
• End of 2015
– Deployment in Valencia with Emivasa, Grupo Aguas de Valencia.
– 650'000 smart meter in 2015 (490'000 already deployed)
– Access to 2500+ smart meter at 1h resolution
• 2016-17
– Deployment in London with Thames Water
• Long term investment: 3 M smart meter before 2030 (40’000 in 2015)

15. thank you
http://www.smarth2o-fp7.eu/
@smartH2Oproject
#SmartH2O
@NRMPolimi
piero.fraternali | giorgia.baroffio | andrea.cominola
@polimi.it
Politecnico di Milano
Department of Electronics,
Information and Bioengineering