Non-Revenue Water Monitoring and Reduction Using Advanced LTE Communications Gwinnet County GA: Difference between revisions

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{{ActionCluster
{{ActionCluster
 
|image=researchproject2.jpg
| title            = Non-Revenue Water Monitoring and Reduction Using Advanced LTE Communications, Gwinnet County GA Department of Water Resources
|team=Jacobs, Qualcomm, ATT, Neptune Meters, Capstone Meters, Trimble/Telog, Krohne, Fathom
| team             = Jacobs (formerly CH2M Hill), Qualcomm, AT&T, Neptune Meters, Capstone Meters, Trimble/Telog, Krohne, Fathom
|leader=Kenneth Thompson
 
|imagecaption=Water Monitoring
| leader           = Ken Thompson
|municipalities=Gwinnett County GA
| email            = Ken.Thompson1@jacobs.com
|status=Development
| image            =
|description=Install the first LTE communications base instrumentation in a pilot area and develop algorithms for understanding the elements of non-revenue water (lost water) as a means to reduce the cost of water delivery, improve management of scarce water resources, improve system operations, and save money for customers. The pilot will use advanced instrumentation with embedded LTE communications chips, such as smart water meters and pressure sensors to produce data to be used in the development of the software algorithms.
| imagecaption     =  
|challenges=* Development of advanced non-revenue water algorithms
| municipalities   = Gwinnett County, GA
<!--, Regional Water Authority-->
| status           = 
| website          =  
| download          =
 
| description       =  
Install the first LTE communications base instrumentation in a pilot area and develop algorithms for understanding the elements of non-revenue water (lost water) as a means to reduce the cost of water delivery, improve management of scarce water resources, improve system operations, and save money for customers. The pilot will use advanced instrumentation with embedded LTE communications chips, such as smart water meters and pressure sensors to produce data to be used in the development of the software algorithms.
 
| challenges       =  
* Development of advanced non-revenue water algorithms
* Correlating data with real water loss (pipeline leaks, theft, inaccurate metering) to verify algorithms
* Correlating data with real water loss (pipeline leaks, theft, inaccurate metering) to verify algorithms
 
|solutions=TBD
| solutions             =  
|requirements=* Identify the pilot location
 
| requirements       =  
* Identify the pilot location
* Procure and install smart meters and pressure sensors
* Procure and install smart meters and pressure sensors
* Develop a baseline for water flow and pressure being served to the pilot area
* Develop a baseline for water flow and pressure being served to the pilot area
Line 32: Line 18:
# Real time assessment to differentiate between leaks, theft and inaccurate meter reads
# Real time assessment to differentiate between leaks, theft and inaccurate meter reads
* Validate algorithms
* Validate algorithms
 
|kpi=* Reduction in leaks on customer premises by 75%
 
 
| kpi               =  
* Reduction in leaks on customer premises by 75%
* Reduction in non-revenue water by 75%
* Reduction in non-revenue water by 75%
* Reduction in water treatment and delivery costs associated with energy savings
* Reduction in water treatment and delivery costs associated with energy savings
 
|measurement=* Comparison of DMA meter with sum of residential meters to identify total NRW changes throughout the project
 
| measurement       =  
* Comparison of DMA meter with sum of residential meters to identify total NRW changes throughout the project
* Comparison of projected Demand Profile versus Actual Demands for DMA meter and residential meters
* Comparison of projected Demand Profile versus Actual Demands for DMA meter and residential meters
* Evaluation of pressure profile changes and development of unique profiles for theft, pipeline breaks, and small pipeline leaks
* Evaluation of pressure profile changes and development of unique profiles for theft, pipeline breaks, and small pipeline leaks
 
|standards=* Use of open standards for data transfer, analytics software, and visualization tools
| standards         =  
* Use of open standards for data transfer, analytics software, and visualization tools
* Use of cellular standards for 3G and LTE
* Use of cellular standards for 3G and LTE
* The total system approach that is developed could be readily modified for use in other water distribution systems worldwide
* The total system approach that is developed could be readily modified for use in other water distribution systems worldwide
 
|cybersecurity=TBD
 
|impacts=* Reduction in energy use for drinking water treatment and distribution associated with water reduction
| cybersecurity         =  
 
| impacts                 =  
* Reduction in energy use for drinking water treatment and distribution associated with water reduction
* Reduction in use of chemicals and residuals for water treatment associated with water reduction
* Reduction in use of chemicals and residuals for water treatment associated with water reduction
* Reduction in cost of water treatment and distribution associated with water reduction
* Reduction in cost of water treatment and distribution associated with water reduction
 
|demonstration=* Phase I Pilot/Demonstration:
 
| demonstration       =
* Phase I Pilot/Demonstration:
Pilot area defined and DMA meter serving the pilot area installed. Baseline established for water being served into the pilot area and compared with amount being currently billed to the customers to establish baseline NRW. Pressure sensors installed and baseline established for pressure profile in the pilot area.
Pilot area defined and DMA meter serving the pilot area installed. Baseline established for water being served into the pilot area and compared with amount being currently billed to the customers to establish baseline NRW. Pressure sensors installed and baseline established for pressure profile in the pilot area.


* Phase II Deployment:
* Phase II Deployment:
All smart meters installed. Algorithms developed and validated. Enhanced pressure profile developed. Reports produced defining the approach and savings in energy, chemicals and cost.
All smart meters installed. Algorithms developed and validated. Enhanced pressure profile developed. Reports produced defining the approach and savings in energy, chemicals and cost.
 
|chapter=Smart Water
| supercluster           = Utility
|supercluster=Utility
| year                   = 2017
|year=2016, 2017
 
|title=Non-Revenue Water Monitoring and Reduction Using Advanced LTE Communications, Gwinnet County GA Department of Water Resources
|email=Ken.Thompson1@jacobs.com
}}
}}
[[Category:Year_2016]]

Latest revision as of 02:02, January 25, 2023


Non-Revenue Water Monitoring and Reduction Using Advanced LTE Communications Gwinnet County GA
GCTC logo 344x80.png
Researchproject2.jpg
Water Monitoring
Team Organizations Jacobs
Qualcomm
ATT
Neptune Meters
Capstone Meters
Trimble/Telog
Krohne
Fathom
Team Leaders Kenneth Thompson
Participating Municipalities Gwinnett County GA
Status Development
Document None

Description

Install the first LTE communications base instrumentation in a pilot area and develop algorithms for understanding the elements of non-revenue water (lost water) as a means to reduce the cost of water delivery, improve management of scarce water resources, improve system operations, and save money for customers. The pilot will use advanced instrumentation with embedded LTE communications chips, such as smart water meters and pressure sensors to produce data to be used in the development of the software algorithms.

Challenges

  • Development of advanced non-revenue water algorithms
  • Correlating data with real water loss (pipeline leaks, theft, inaccurate metering) to verify algorithms

Solutions

TBD

Major Requirements

  • Identify the pilot location
  • Procure and install smart meters and pressure sensors
  • Develop a baseline for water flow and pressure being served to the pilot area
  • Develop algorithms for:
  1. Individual meter demand profiles and system wide demand profile
  2. Real water loss
  3. Real time assessment to differentiate between leaks, theft and inaccurate meter reads
  • Validate algorithms

Performance Targets

Key Performance Indicators (KPIs) Measurement Methods
  • Reduction in leaks on customer premises by 75%
  • Reduction in non-revenue water by 75%
  • Reduction in water treatment and delivery costs associated with energy savings
  • Comparison of DMA meter with sum of residential meters to identify total NRW changes throughout the project
  • Comparison of projected Demand Profile versus Actual Demands for DMA meter and residential meters
  • Evaluation of pressure profile changes and development of unique profiles for theft, pipeline breaks, and small pipeline leaks

Standards, Replicability, Scalability, and Sustainability

  • Use of open standards for data transfer, analytics software, and visualization tools
  • Use of cellular standards for 3G and LTE
  • The total system approach that is developed could be readily modified for use in other water distribution systems worldwide

Cybersecurity and Privacy

TBD

Impacts

  • Reduction in energy use for drinking water treatment and distribution associated with water reduction
  • Reduction in use of chemicals and residuals for water treatment associated with water reduction
  • Reduction in cost of water treatment and distribution associated with water reduction

Demonstration/Deployment

  • Phase I Pilot/Demonstration:

Pilot area defined and DMA meter serving the pilot area installed. Baseline established for water being served into the pilot area and compared with amount being currently billed to the customers to establish baseline NRW. Pressure sensors installed and baseline established for pressure profile in the pilot area.

  • Phase II Deployment:

All smart meters installed. Algorithms developed and validated. Enhanced pressure profile developed. Reports produced defining the approach and savings in energy, chemicals and cost.