1. Vers une Gestion
Intelligente des
Réseaux Urbains
Bruno Nguyen, Director of Operation
9 Septembre 2011, Lille Frank Montiel, Head of SCADA Research &
Development

2. RISK ANALYSIS
Governance
Public Education
Regulation
Sustainable Development
Eco-Risk
System Context
Asset Management Climate Change
Crisis Management Public Concern
From Resource to Consumers Globalization
AvailableTechnol. Developt
Risk analysis: Cross assessment of 3 dimensions System-Context-Governance

3. Urban Challenges & Climate Change
Impacts
Growing public demand for reliable,
affordable, safe, and environmentally
sustainable metropolitan systems.
Rising concerns with regard to growing
threats and uncertainties of climate
change impacts.
Urban Challenges of economic Natural Disaster – Tsunami Indonesia
globalization, growing environmental
concerns, increasing financial constraints
in public infrastructure investments.
Growing needs for promoting priority
issues and concerns of local governments
at the global and/or national level to
effectively affect current trends in
emerging environmental sustainability
policy and regulations
Smart Buildings for Sustainable Energy

4. Paris Water System
Water distribution network characteristics
Distribution network
•
A very gridded network
•
95 % of the pipe are visible
Non
drinking
water pipe
Drinking water
pipe
Customer
pipe
Sewer
Waste water

5. The Dispatching Center

6. CHLORSCAN SENSORS IN THE DISTRIBUTION SYSTEM
• Since 2004, 104 Chlorscans sensors have been
operated online and in real time throughout Paris.

7. Real time pipe burst detection
Pipe Break detection by observing brutal real-time pressure fall and rising flow
- Low alarm pressure threshold on the scada system: all the real time pressure are
defined in the scada system with such a threshold alarm.
- High and low alarm flow threshold on the scada system.
This method can detect brutal change in water distributed volume, it is less sensitive to little
leakage.

8. District Metering Area Definition
30 sub areas have been defined for the city.
180 flow-meters used (real time and differed time).
All the water transfers between areas is count and manual valves are closed
if necessary.

9. Leakage Detection
Leakage detection with increasing average night flow and daily distributed volume
Most of leakage detection are detected with the average night flow and confirmed with the
daily distributed volume.
Rising detection has to be correlated with operation events (it can be due to filling swimming
pool for example).
Average night flow Daily distributed volume

10. AMR systems in Paris
The meter reading systems developed and installed in Paris since 2004 by Suez
and Veolia differ from one another. On the Right Bank of the Seine (2/3 of Paris),
Veolia has chosen a bi-directional short-range system; whereas Suez on the Left
Bank (1/3 of Paris) preferred uni-directional long-range system.
AMR: How does it work ?
Short Range System Véolia
Repeater 64 280 meters
Véolia System
GPRS Network
Radio Short Range
With Repeater 38 787 repeaters
Concentrator
Central
System 579 concentrators
Radio Suez System
GPRS Network
Long Range System Suez
Module Radio Long Range
Impulses
28 162 meters
Emitter
8 010 boosters
219 concentrators
Mechanical Meter
The information of the 93 000 meters are transmitted once a day.
The information of these meters are aggregated per area and allow the short differed time
comparison with the input water in order to identify leakage growth.
Data are available after three days.

11. AMR-DMA Pipe burst detection example
Comparison between Daily water distributed Daily water losses calculated trend in a sub
volume trend and Daily water consumption network.
volume trend in the same sub network.

12. SMART GRIDS FOR THE WATER
SYSTEM IN PARIS ?
What is the limitation of the current state
practice and the business case for Smart
Grids ?
è
Optimization of Operational Management (operator’s
performance)
è
Redefinition of Asset Management – best choice with
uncertainties assessment (operator’s performance)
è
Efficient Master Planning – best investment in larger
context prevision (system performance)

13. SMART GRIDS FOR THE WATER
SYSTEM IN PARIS ?
What are the challenges and priority needs
for which Smart Grids is useful ?
è
Water losses reduction in the distribution pipe network
by active leakage detection and repair;
è
Pipe burst prevention and reduction of their social costs
by efficient renewal of the conduits;
è
Reduction of water quality defaults identified by
sampling analysis and customer’s complaints;

14. SMART GRIDS FOR THE WATER
SYSTEM IN PARIS ?
S teur 2
ec
S teur 3
ec
Pipe
Distribution
Network Secteur1
S teur 4
ec

15. SMART GRIDS FOR THE WATER
SYSTEM IN PARIS ?
Roadmap
è
Added values for short, medium & long term ?
è
How to benchmark ? Which indicators ?
(economic, ecologic, sociologic…)
è
Development of integrated system modeling
è
Where to start ?

16. The SUNRISE Project
Fields of Interest
• Real time supervision and
data acquisition (AMR).
• Improved wireless
communication system.
• Multi utilities networks
(Water, Energy...).
• Lille University is an open
field for researcher.
• Valorisation of Eau de Paris
expertise in SCADA systems.
• Water Smart Grid research
project.
• Application in Paris Therefore, the SUNRISE Project in
network. Lille is a real opportunity

17. Conclusion
Technology trends and new concepts for water integration in the global
urban management are deemed to provide future improvements through
better asset management, new services to the customers and better
response to consumer’s expectations.
Smart Grids have shown results in the Energy business; application in the
Water business is still awaited.
The water infrastructure deployed in Paris already offers many advantages
in the daily operation of the system, but more can be done. According to the
experience of Eau de Paris, three particulars points of the leakage detection
process can considerably be improved:
•
Amelioration of the whole system of AMR transmission in order to make the
existing system become ‘Real-time’ system.
•
Development of anomalies detection process using new algorithms.
•
Develop and establish appropriate response based on identified anomalies.
Lille university’s water network will be a very relevant place to make possible
a project for developing such a whole process.

18. Thank you for your attention