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SWAN ARCHITECTURE
ANDREW BURROWS CTO & Co-Founder i2O Water
SWAN ARCHITECTURE WORK GROUP
Utilities
• David Ward, Anglian Water
• Ding Carpio, Manila Water Company
• John Douglas, Northumbrian Water
• Keith Hilson, South East Water UK
• Louise Dudley, Queensland Urban Utilities
• Nina Meyers, Queensland Urban Utilities
• Paul Belz, Queensland Urban Utilities
• Tracy Minall, Queensland Urban Utilities
• Peter Gallant, Veolia Water
• Philip Onunkwo, South East Water
Technology providers
• Andrew Burrows, I2O (WG Chair)
• Christopher Phillips, I2O
• David Persson, ABB
• Haggai Scolnicov, TakaDu
• Jamie Longman, Sensus
• Laurie Reynolds, Aquamatix
• Ofer Cohen, Bermad
• Paul Chandler, Gutermann
• Paul Linford, Syrinix
• Simon Bunn, Derceto
• Zohar Yinon, Hagihon
SWAN Researchers
• Deepti Das, SWAN
• Amir Cahn, SWAN
GOAL
• To define the architecture of Smart Water Distribution Networks mapped through challenge areas to the root business drivers
• Develop tools to help water utilities to define the most appropriate architecture for their distribution network and challenges
• Provide guidelines for establishing the return on investment
PROCESS
DRIVERS
• Research business Drivers across broad geographies
• Research challenge Areas to address business drivers
Solutions
• Research technologies and solution areas
• Map the many to many relationships of technologies and challenges
• Develop SWAN architectures that address challenge areas
• Collate case Studies
Conclusion
• Identify benefits
• Identify limitations and technology gaps
• Recommendations
SMART WATER NETWORK
A smart water network is a fully integrated set of products, solutions and systems that enable water utilities to:
• Remotely, continuously and automatically monitor and diagnose problems, pre- emptively prioritize and manage issues and remotely control and automatically optimize all aspects of the water distribution network using data-driven insights from multiple data streams
• Comply transparently and confidently with regulatory and policy requirements on water quality and conservation
• Provide water customers with the information and tools they need to
make informed choices about their behaviors and water usage patterns
DRIVERS
BUSINESS DRIVERS
Customer Service
Revenues
Capital Expenditure
Operational Expenditures
Supply constraint
SMART WATER
NETWORK
Environmental & Government Regulations
Weather/Climate
Change
Competition
Source: Workgroup research
BUSINESS DRIVERS
Customer Service
Revenues
Capital Expenditure
Operational Expenditures
Supply constraint
SMART WATER
NETWORK
Environmental & Government Regulations
Weather/Climate
Change
Competition
Operational Expenditures
Workgroup research
50% of global water utility spending is on OpEx 56% is on distribution OpEx
44% is on production OpEx
BUSINESS DRIVERS
Customer Service
Revenues
Capital Expenditure
Operational Expenditures
Supply constraint
SMART WATER
NETWORK
Environmental & Government Regulations
Weather/Climate
Change
Competition
Operational Expenditures
Workgroup research
Distribution OpEx Major components
66% Repair and maintenance On average utilities spend 20% of their annual spending on Repair and Maintenance.
Utilities claimed that approx. 80% of Repair and maintenance was focused around fixing leaks and bursts.
9% Pressurisation
6% Quality monitoring
6% Chemicals
Source: Water 2020 – EMBA4web - Sensus
BUSINESS DRIVERS
Customer Service
Revenues
Capital Expenditure
Operational Expenditures
Supply constraint
SMART WATER
NETWORK
Environmental & Government Regulations
Weather/Climate
Change
Competition
Operational Expenditures
Workgroup research
Production OpEx Major components
35% Energy
30% Materials
20% Labour
Source: Water 2020 – EMBA4web - Sensus
BUSINESS DRIVERS
Customer Service
Revenues
Capital Expenditure
Operational Expenditures
Supply constraint
SMART WATER
NETWORK
Environmental & Government Regulations
Weather/Climate
Change
Competition
Workgroup research
47% of global utility spending is on CapEx 59% is Pumps, meters and valves
41% is pipes
Capital Expenditure
Source: Workgroup research
BUSINESS DRIVERS
Customer Service
Revenues
Capital Expenditure
Operational Expenditures
Supply constraint
SMART WATER
NETWORK
Environmental & Government Regulations
Weather/Climate
Change
Competition
Workgroup research
Increasing pressure to improve customer satisfaction
3% of global utility spending is Customer service
Customer Service
Source: Workgroup research
BUSINESS DRIVERS
Customer Service
Revenues
Capital Expenditure
Operational Expenditures
Supply constraint
SMART WATER
NETWORK
Environmental & Government Regulations
Weather/Climate
Change
Competition
Supply constraint
Environmental & Government Regulations
• According to the World Bank, aging water distribution networks results in annual water losses (NRW) estimated globally at 48.6 billion cubic meters
• Regulators are setting leakage reduction
targets and imposing fines for failure to comply.
• Water stress and aging infrastructure,
driving solutions to reduce water losses and enable water conservation.
Source: Growing-Blue
Weather/Climate
Change
CHALLENGES
Challenge Areas % Key Performance Measures
REDUCE LEAKAGE 38% + Leakage Target, Energy, SIM, Chemical Costs
REDUCE BURSTS 28% Operating Costs, Serviceability, SIM
MINIMISE ENERGY 12% + Operating Costs, Production Costs
IMPROVE LEVEL OF SERVICE 8% SIM, Regulatory
ACHIEVE QUALITY TARGETS
4% SIM, Regulatory, Security
IMROVE COST EFFECTIVENESS (Field Ops) 4% Opex
Demand optimisation/ reduction +
MINIMISE APPARENT LOSSES Leakage target, Revenue
EXTEND AGING INFRASTRUCTURE LIFE ++ Operating Costs, Capital Expenditure
IMPROVE HEALTH & SAFETY Accident frequency rates, CHaSPI (UK)
PROTECT ENVIRONMENT +++ Carbon Footprint, Greenhouse gases, Sustainable resources
NETWORK SECURITY IT and bio/chemical attacks
CHALLENGES – WATER UTILITIES Our research identified the following as the key challenges to address drivers faced by utilities globally. Source: Workgroup research, Takadu research
MAPPING BUSINESS DRIVERS TO CHALLENGES
Business Drivers
Challenge
Weather/ Climate Change
Demand Forecasting
Losses Customer
Service
Business Driver
Challenges
Totex
Losses
Customer Service
Regulatory Revenues
TECHNOLOGIES
TECHNOLOGY SOLUTIONS
Physical layer Sensing and
Control Communication and Collection
Data Management and Display
Data Fusion and Analysis
Network topology • District metering
areas • Pressure
management areas
Network assets • Pipework • Pressure Reducing
Valves • Pumps • Customer meters
• Flow logging • Quality sensors • Pressure logging • Acoustic logging • Acoustic
Correlators • Energy sensors • Smart Meters • PRV control • RTU/ PLC • Variable speed
drives
• Fixed cable network
• Cellular • WiFi • Long-range radio • Mesh Radio
• Databases • GIS • Telemetry • SCADA • Remote control • Meter Data
Management • ERP • Billing
• Forecasting • Condition
monitoring • Operations
prioritisation • Live modeling • Pressure
optimisation • Reservoir
optimisation • Pump
optimisation
Source: Workgroup research
ARCHITECTURE
Architecture
• Drivers
• Challenge areas
• Technologies
How to combine technologies to create a SMART solution architectures that optimally addresses the challenges and drivers?
Solution Areas e.g. ALC..
DMA Bulk
meter
Flow loggers
Noise loggers
GSM SMS
Telemetry System
ALC Prioritisation
GSM GPRS
RADIO
MAPPING TECHNOLOGIES TO SWAN LAYERS
Customer Meter
Smart customer
Meter
Pressure loggers
Wired Mesh radio
Data repository
Basic reporting & visualisation
Bench- Marking
Noise correlators
Burst awareness
Network Anomaly
Burst pin-pointing
Works optimisation
CASE STUDY : Project - Eislingen
Problem Statement
POTENTIAL SOLUTION: • Permanent noise correlators
CHALLENGES:
Business challenges • Identify bursts quickly • Prioritise bursts • Pinpoint bursts
Minimize burst “visibility, find and fix” time
Representation of the architecture
Layer 5 Data Fusion, Analysis &
Optimization
Layer 4 Data Management
& Display
Layer 3 Communications
Layer 2 Sensing & Control
Layer 1 Infrastructure
Open network/ DMA/ PMA
EVENT PRIORITIZATION
gprs
radio
relay
Burst pinpointing
Data display and reporting
Data Storage
Noise Correlator
radio
Noise Correlator
Noise Correlator
radio
Source: Gutermann
PROJECT - EISLINGEN
PayBack Period and ROI:
Operating costs:
Reduced by 26 working weeks the leak detection operations
= 26 x ca. €1900
= ca. € 50,000 per year
Water costs:
Reduction of MNF by 5 l/s
= 160,000 cubic meters water per year
x €0.69 per cm production cost
= € 108,800 per year
Total measured cost reduction: = ca. € 160,000 per year , PayBack : 2-3 months
Source: Gutermann
Source: Gutermann
CASE STUDY : Project – Syabas Malaysia
Problem Statement
POTENTIAL SOLUTION
• Automatic pressure optimisation
CHALLENGES:
• Reduce real losses • Reduce burst frequency • Extend asset life
• Urgent need to reduce real losses
• Forecast shortfall • Regulative pressure • Customer expectations
Forecast shortfall - Minimize real losses
Representation of the architecture
Layer 5 Data Fusion, Analysis &
Optimization
Layer 4 Data Management
& Display
Layer 3 Communications
Layer 2 Sensing & Control
Layer 1 Infrastructure
Pressure Optimisation
algorithm
GPRS
Data display and reporting
Data Storage
PRV Controller & Pressure and Flow logger
Pressure logger
PRV PMZ
GPRS
METER
FEEDBACK GPRS
Source: i2O Water
PROJECT - SYABAS
+ Largest water concessionaire in Malaysia
(supplies 7 million consumers)
+ 229 DMAs with i2O PRV control
+ Additional 200 systems being installed
and optimised
+ ROI on first 229 systems 7.1 months
+ Latest TDF reduced by 51 MLD
51 MLD
TDF reduction from first 229 systems
Source: Syabas Water, Malaysia
CASE STUDY: Yarra Valley Water (Melbourne, AU)
Problem Statement
POTENTIAL SOLUTIONS: • From 1995-2011, YVW adopted the following nine
solutions:
o Implement zone Metering o Improve Bulk Meters o Pressure Management o ALC o Immediate customer shutoff o Customer Meters o Reservoir leakage sensing o Water Network Monitoring
Challenge:
o Urgent need to reduce non-revenue water o High water cost o High energy cost o High field opex cost o Regulative pressure o Customer expectations
There is a constant need to reduce non-revenue water.
Source: Takadu / Yarra Valley
Business Drivers
High Water Costs
High Energy Costs
Improve Operational
Efficiency
Maintenance Costs
Regulation Benchmarking Customer
Expectations
Challenge NRW REDUCTION
Solution Areas
Improved Bulk Meters
Zone
Metering
Pressure
Management
Water Network
Monitoring
Layer 2 Sensing &
Control
Layer 1 Infrastructure
Layer 3 Communications and Collection
Layer 4 Data
Management & Display
Layer 5 Data Fusion, Analysis &
Optimization
Pressure
Flow
SCADA
Radio
GSM
GIS
Control
DMAs
Custr Meters
Pressure
Flow
Radio
GSM
SCADA
GIS
DMAs
Meters
PMAs
Pressure
Flow
Control
Radio
GSM
SCADA
GIS
Hydraulic Modelling
DMAs
Meters
PMAs
Pressure
Flow
GPRS
GSM
SCADA
GIS
Automated Monitoring
TECHNOLOGY STACK
DMAs
Meters
PMAs
Source: Takadu / Yarra Valley
Representation of the architecture
Layer 5 Data Fusion, Analysis &
Optimization
Layer 4 Data Management
& Display
Layer 3 Communications
Layer 2 Sensing & Control
Layer 1 Infrastructure
Hydraulic model
GPRS/ Radio
GIS SCADA
PRV Controller & Pressure and Flow logger
Pressure logger
PRV DMA & PMZ
GPRS/ Radio
METER
Customer meters
Automatic monitoring
VSD Pump
Pump RTU Pump VSD
Source: Takadu / Yarra Valley
YVW NRW REDUCTION
28 Gl 3
4
1 1 3 Improved
Bulk/Custom MetersZone Metering
PressureManagementCustomer Meter
Easyfill
• The biggest reduction in NRW was observed by installing Bulk and customer meters, Zone metering and pressure management
• Increased knowledge of the network • Better informed operational, maintenance and
planning decisions
• Increased efficiency of human operators
• Reduced the run-time of a leak
• Reduced the man hours spent searching for leaks
• Reduced repair costs through early intervention
• Improved customer relations
Source: Takadu / Yarra Valley
YVW NRW REDUCTION
Since 1995, YVW has decreased NRW by 75%
Source: Takadu / Yarra Valley
Next stage
Build detail around • Drivers, challenge areas and technology solutions • Create architecture models and guidelines against
combinations of challenge areas. • Create a common language • Map the “many – many” relationships
– Create ROI models for individual and combination solutions.
• Create case studies • Create papers and tools for SWAN members
HTTP://WWW.SWAN-FORUM.COM/WORKGROUPS.HTML
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