© 2009 IBM Corporation Advance Water Management Smart Water December 2009 Pnina Vortman IBM Haifa...

© 2009 IBM Corporation

Advance Water Management

Smart Water

December 2009

Pnina Vortman

IBM Haifa Research Lab

IBM Confidential


© Copyright IBM Corporation 2009

Organizations will manage their environmental impactby addressing three critical resources:

CO2 emissions contribute to climate change, which impacts water systems.

Energy production results in CO2

emissions.

Water is needed to generate energy

and energy is need to provide water.

WATERWATER

CARBONCARBONENERGYENERGY

IBM Confidential



Something profound is happening….

INSTRUMENTED

We now have the ability to measure, sense and see the exact condition of practically everything.

INTERCONNECTED

People, systems and objects can communicate

and interact with each other in entirely new

ways.

INTELLIGENT

We can respond to changes quickly & accurately, getting

better results by predicting and optimizing for future events.

IBM Confidential



Water Management – what do we mean ?

When you say ‘water’ there are many issues involved: – Sources: traditional, alternative

• Traditional: Lakes, Rivers, Aquifer, Wells• Alternative: Desalination, Recycled, Types

– Impact on the environment• Must monitor to be able to measure and know• Must be able to control in real-time

– Quality of water• Various quality based on usage : drinking, agriculture, industrial

– Recycling• Water purification for reuse in agriculture and industrial• Water purification to protect the underground water and rivers• Water reuse for residential use

– Wastewater• Protecting the environment• Monitor to prevent contamination

IBM Confidential



Water Sources

Rivers and lakes

Underground water

Desalination

Water sensors and meters

Integrated View of Intelligent Water Management

Co

lle

cti

on

Asset Management with QoS Extension

Real-time Analytics

Historical Analytics

Water Network Design

Optimized Leakage ReductionOptimized Electrical PowerOptimal Water BlendingProactive Water Maintenance

QoS Specification

Purification plant

IBM Confidential



Alternative Sources of Water – Desalination Plants

Must monitor to understand the impact of desalination on the environment. How do we get rid of the brine ?

IBM Confidential



Fighting Floods

We need to be able to predict the weather within small areas. How can we help ? Require data collection.

IBM Confidential



Fighting Draughts

We need to save water, find alternatives, control usage, predict the weather within small areas and conserve rain water. Optimization, simulation, and forecasting.

IBM Confidential



Strategic Water Information Management Platform

Provides automated sensing of physical environments

Provides water quality, quantity, integration, storage, analysis, modeling, and a management dashboard on a local or regional basis

Provides records management and reporting capabilities for regulatory and compliance requirements.

Provides energy usage information to pinpoint energy efficiency opportunities related to water

Provides advanced asset management and advanced meter management capabilities

Provide intelligence to proactively manage risk related to extreme weather events

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By measuring, monitoring and managing environmental systems, decision makers will have more knowledge of how their decisions will influence the environment & business.

Managing & Monitoring Water Systems

Paraguay-Paraná River Basin, BrazilParaguay-Paraná River Basin, Brazil

IBM Confidential



Smart Water Management system in residential areas

Machine Learning based water management to detect anomalies, analyze trends, understand behavioral models, and provide usage predictions and inputs to optimization.

Monitoring and integrate information from sewer and water systems in real-time

Collect and analyze information from water metering in real-time

Machine Learning based analysis

IBM Confidential



Water Analytics for generating Usage Patterns, Detect Anomalies, Predict and Forecast Water Demand

Goals– Understand usage patterns to detect anomalies and predict demand – Distribute energy consumption to minimize cost based on the usage patterns– Adapt water pressure based on usage patterns

Technology solution– Machine Learning and analytics which analyze water usage data from smart

metering and smart valves/pumps generating reports and generating alerts when anomaly is detected

Results– Analytical reports, alerts, and dashboard based on smart metering data to

understand usage patterns, applied clustering analysis and provided prediction– Using GIS, map usage patterns over the geographic map based on household

Scenarios– Water utility command center receives alert, monitors and observe an anomaly in

usage. Message is sent to customer– Customer checks problem and fix it. High customer satisfaction.

IBM Confidential



Example: Before and after leakage fixing

Time-of-day analysis shows the leak drowned the actual demand

IBM Confidential



Water Leakage Reduction Through Dynamic Pressure Management – with company in Israel

Problem Overview:– Significant amounts of water are lost due to leakage in water networks– The leakage can be reduced by lowering the pressure of the supplied water– However, sufficient pressure must be maintained to provide the required time varying

demand for water flow Solution Approach:

– Minimize leakage by dynamic control of valves so as to reduce pressure while providing required flow• Utilizes Combination of forecasting, hydraulic simulation and optimization

models/techniques– Includes real time monitoring and control infrastructure to constantly adapt based on actual

consumer water flow requirements Benefit: Significant reduction in water leakage

IBM Confidential



Pressure Setting Results

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1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49

Non Regulated Pressure

Maximum Regulated Pressure

Regulater Pressure

IBM Confidential



Quality of Service in Water Systems

Need to agree on pressure and quality levels of water for residential, commercial, and industrial

Asset management systems manage and store information about every element in the water network systems such as pumps, valves, pools, meters

Asset management systems can be expanded to “remember” incidents and location of every asset in the water network

Can introduce maintenance optimization based on location and state

Can optimize power cost for pumping water Leakage detection combined with GIS system

can assist in minimize network closure Integrated with usage analytics, can control

pressure and adapt dynamically Integrated with quality sensors, can minimize

the contamination expansion

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The Water for Tomorrow Project

Combine science-driven conservation with I/T expertise and computing power

Build a novel software modeling framework to simulate the behavior of river basins around the world

Inform policy and management decisions that conserve the natural environment and benefit the people who rely on these resources

Sample questions:- What impact will development have on water availability for

wetlands and farming downstream? - Will clear-cutting a forest in the upper part of a river's

watershed imperil fish stocks local people depend on for food? - Management tradeoffs including crop production, water

balance, water quality, carbon storage, biodiversity and economic metrics.

Data: climate, rainfall, land cover, soil moisture, land use, etc.

Software:- Scenario forecasting tools- Integrative modeling framework- 3-D visualization

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The Beacon Institute

Mission: “To create a global center for interdisciplinary research, policy-making and education regarding rivers, estuaries and their connection with society.”

–The goal: turn all 315 miles of the Hudson river into a distributed network of sensors that will collect and analyze biological, physical, and chemical information–Create a river and estuary observatory through a collaborative program of technology innovation and development aimed at advancing science, management, and education–Link models to the river ecosystem to understand phenomena across a range of spatial and temporal scales

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Smart Bay—Galway Bay, Ireland

Collaboration with the Marine Institute, Ireland- A research, test and demonstration infrastructure for monitoring and managing aquatic

environmental data such as tidal flow, wave heights, temperature, and phytoplankton via an integrated network of sensors, robotics and computational technology distributed throughout the Bay.

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Intelligent Sensor Networks - Ijkdijk

• Dutch “Smart Levee” Test Site

• Collaboration with Ijkdijk Foundation, Deltares & TNO

•6 meters high (coastal levee category)•100 meters long•30 meters wide

Active monitoring via sensor network to gain insight on levee internal stability

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Advanced Water Management - Utility Scale

4) Wireless network links meters and sensors to central console

6) Web console acts as a control center for integrating all water data and enabling drill down on any parameter related to water availability, quality or associated energy costs. Alerts generated if necessary. Multiple locations can be rolled up.

3) Data are also drawn from external sources such as historical databases or remote sensing / geographical surveys

1) Data collection may begin upstream from the treatment plant

2) Sensors are deployed on all water inlets and/or outlets to detect key contaminants. Discharge outlets are also metered. Data are also drawn from SCADA systems. (Manual inputs may also be used)

5) Weather, climate and hydrological models provide additional insight into water quality or availability impacts

7) Advanced analytics provides additional predictive capability

All assets of the same type in this area highlighted in blue

Search for all assets of the Type ‘natural channel’ with condition = 3 in this area. Results are highlighted in blue

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IBM 200 mm and 300 mm wafer fabs – Water management

Challenge Reduce water consumption (and associated need for

energy, chemicals, maintenance and labor) to reduce operating cost and minimize environmental impacts

Leverage end-to-end data acquisition, storage and visualization techniques to monitor water usage and improve efficiency

Approach Implemented data collection and storage

infrastructure: sensors, IT network and servers Statistical process control techniques used to

continually analyze vast amounts of operational data and present information in efficient, concise interface

IBM’s Green Sigma™ methodology breaks down water usage by process:

– Dashboards convey key process indicators– Identifies process improvements that reduce water

consumption and provide other benefits, such as reduced electrical power consumption, heat recovery, cooling load reduction, process efficiency etc.

ResultsIBM has achieved over $3M in annual savings by reducing water usage by 27% and increasing manufacturing production over 30%

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Thank-you!

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