29 Septembre 2011, Lille

Vers une Gestion Intelligente des

Réseaux UrbainsBruno Nguyen, Director of Operation

Frank Montiel, Head of SCADA Research & Development

Risk analysis: Cross assessment of 3 dimensions System-Context-Governance

Context

Climate ChangePublic ConcernGlobalization

AvailableTechnol. Developt

System

Asset ManagementCrisis Management

From Resource to Consumers

Governance

Public EducationRegulation

Sustainable Development

Eco-Risk

RISK ANALYSIS

Urban Challenges & Climate Change Impacts

Growing public demand for reliable, affordable, safe, and environmentally sustainable metropolitan systems.

Natural Disaster – Tsunami Indonesia

Smart Buildings for Sustainable Energy

Rising concerns with regard to growing threats and uncertainties of climate change impacts.

Urban Challenges of economic 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

Water distribution network characteristics

Distribution network• A very gridded network• 95 % of the pipe are visible

Sewer

Drinking water pipe

Non drinking

water pipe

Waste water

Customer pipe

Paris Water System

The Dispatching Center

CHLORSCAN SENSORS IN THE DISTRIBUTION SYSTEM

• Since 2004, 104 Chlorscans sensors have been operated online and in real time throughout Paris.

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.

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.

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.

Average night flow Daily distributed volume

Rising detection has to be correlated with operation events (it can be due to filling swimming pool for example).

Leakage Detection

AMR systems in Paris

Radio Module

Impulses Emitter

Mechanical Meter

Véolia System

Radio Short Range

With Repeater

Suez System

Radio Long Range

Concentrator

RepeaterGPRS Network

GPRS Network

Central System

AMR: How does it work ?Short Range System Véolia

64 280 meters

38 787 repeaters

579 concentrators

Long Range System Suez

28 162 meters

8 010 boosters

219 concentrators

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.

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.

The information of the 93 000 meters are transmitted once a day.

Data are available after three days.

Comparison between Daily water distributed volume trend and Daily water consumption volume trend in the same sub network.

AMR-DMA Pipe burst detection example

Daily water losses calculated trend in a sub network.

What is the limitation of the current state practice and the business case for Smart

Grids ?è Optimization of Operational Management (operator’s

performance)

SMART GRIDS FOR THE WATER SYSTEM IN PARIS ?

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)

What are the challenges and priority needs for which Smart Grids is useful ?

è Pipe burst prevention and reduction of their social costs by efficient renewal of the conduits;

è Water losses reduction in the distribution pipe network by active leakage detection and repair;

è Reduction of water quality defaults identified by sampling analysis and customer’s complaints;

SMART GRIDS FOR THE WATER SYSTEM IN PARIS ?

Secteur1

Secteur2Secteur3

Secteur 4

Secteur1

Secteur2Secteur3

Secteur 4

Pipe Distribution

Network

SMART GRIDS FOR THE WATER SYSTEM IN PARIS ?

Roadmap

è Added values for short, medium & long term ?

SMART GRIDS FOR THE WATER SYSTEM IN PARIS ?

è How to benchmark ? Which indicators ?(economic, ecologic, sociologic…)

è Development of integrated system modeling

è Where to start ?

• 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 network.

Therefore, the SUNRISE Project in Lille is a real opportunity

The SUNRISE Project

Fields of Interest

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.

Conclusion

Thank you for your attention