amr advanced applications – taking it a step beyond
DESCRIPTION
AMR Advanced Applications – Taking it a Step Beyond. David Glenwright AMR Operations & Strategies NARUC July 15, 2007. Topics. Background AMR at PECO Advanced Applications Outage Management Theft Detection Engineering Studies Other Opportunities. Exelon / PECO Background. - PowerPoint PPT PresentationTRANSCRIPT
AMR Advanced Applications – Taking it a Step Beyond
David GlenwrightAMR Operations & Strategies
NARUC
July 15, 2007
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Topics Background AMR at PECO Advanced Applications
• Outage Management• Theft Detection• Engineering Studies• Other Opportunities
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Subsidiary of Exelon Corp (NYSE: EXC) Serving southeastern Pa. for over 100 years Electric and Gas Utility 2,400 sq. mi. service territory Philadelphia and the four surrounding counties Population of approx. 4 million people
Exelon / PECO Background
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Customer ProfileService AreaPhiladelphia & Southeastern PA
2,400 sq. mile service area
CustomersElectric = 1.7 million
Gas = 500 thousand
Automated Meters2.2 million meters on Cellnet Fixed Network
3,000 Large C&I customers on MV- 90 & Metretek
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Scope of AMR at PECO
PECO’s AMR installation project lasted from 1999 to 2003
A Cellnet Fixed Network solution was selected.• 99% of meters are read by the network• Others are drive-by and MV-90 dial-up
During the project, meters were activated at a max rate of 143,500 per month.
Installation was performed by PECO, Cellnet, and VSI.
Cellnet manages the network, performs meter maintenance and provide data to PECO.
All meters are read daily. Additional features include on-demand reads, and event processing.
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Cellnet AMR Network Structure
Cell Master (CM)
Endpoint devices w/CellNet Radio
National Operations Center
(NOC) System
Controller
Wide Area
Network
Local Area Network
MicroCellController (MCC)
ExelonApplications
ExelonApplications
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AMR network components
8,318 MicroCell Controllers
91 Cell Masters
2.2 M Meters~1.6 M Res. Electric~455 K Res. Gas~135 K Com. Electric~42K Com. Gas
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Business Benefits of AMR
Customer InterfaceMinimize inconvenience to customers who have difficult to read metersReduce number of estimated billsImprove ability to answer questions on 1st callProvide more energy usage infoImprove customer satisfaction
Financial ManagementImprove the meter to cash cycle Continuous service - controlsIncrease revenue Improve power factor measurementReduce lost revenue from theft
Operational / System ReliabilityImprove read rate and accuracy Reduce CAIDI by identifying, assessing and responding to outages more efficientlyImprove productivity of field forcesReduce customer call volumesReduce safety incidences•Increase asset utilization•Improve ability to design electric distribution network•Identify precursors to reliability event
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Outage Management
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Outage Example
CALL-9TRF-1
FUSECALL-8
CALL-7
CALL-6
CALL-5
CALL-4
CALL-3CALL-2CALL-1
TRF-2 TRF-1TRF-2
Event Time: 00:00:00 Customers Affected: 000Event Time: 11:27:00 Customers Affected: 001Event Time: 11:31:00 Customers Affected: 002Event Time: 11:35:00 Customers Affected: 003Event Time: 11:35:00 Customers Affected: 004Event Time: 11:38:00 Customers Affected: 005Event Time: 11:38:00 Customers Affected: 006Event Time: 11:43:00 Customers Affected: 018Event Time: 11:49:00 Customers Affected: 019Event Time: 11:49:00 Customers Affected: 086
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Outage Example w/AMRTRF-1
FUSECALL-4
CALL-3 CALL-2CALL-1
TRF-2
TRF-1
TRF-2
LG-1
LG-2LG-3
Event Time: 00:00:00Event Time: 00:00:00 Customers Affected: 000Customers Affected: 000Event Time: 11:27:00Event Time: 11:27:00 Customers Affected: 001Customers Affected: 001Event Time: 11:30:00Event Time: 11:30:00 Customers Affected: 002Customers Affected: 002Event Time: 11:30:00Event Time: 11:30:00 Customers Affected: 003Customers Affected: 003Event Time: 11:30:00Event Time: 11:30:00 Customers Affected: 012Customers Affected: 012Event Time: 11:31:00Event Time: 11:31:00 Customers Affected: 013Customers Affected: 013Event Time: 11:34:00Event Time: 11:34:00 Customers Affected: 014Customers Affected: 014Event Time: 11:34:00Event Time: 11:34:00 Customers Affected: 086Customers Affected: 086
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PECO’s Outage Management Process
AMRLast Gasp
I V R
Call CenterOutageRecord
OMS DispatchAMR
Power-Up
Customer Initiated Calls
AMR Initiated Event
PECOContactsCustomer
AMR PingAdvanced
AssessmentTools
AutomaticProcessing
AMR Initiated EventSCADA
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“Summer Slam” - July 18, 2006
A severe band of thunderstorms caused nearly 400,000 power outages.Determined to be the worst summer storm ever experienced by PECO.
1,200+ single customer outage calls were cancelled without crew dispatch due to meter pings that indicated power-on.
750+ single customer outage calls were escalated into primary events via pings to neighboring customer’s meters. This ensured a properly skilled crew was dispatched the first time.
The pinging and restoration verification tools were used to confirm active jobs were valid prior to crew dispatch. Feedback from the field crews indicated that they felt like they were working more effectively because they had very few assignments that were “OK on arrival”.
Conservative estimates indicate that AMR has helped save in excess of $200,000 in avoided labor costs during this storm.
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AMR Outage Management Summary
Improved outage management performance Quicker response due to last gasp More efficient use of field crews due to pinging (automated &
manual) Validate power restoration times using daily reports Reduced CAIDI by 5.5 minutes in 2005
2004 2005 2006Single Outages Cancelled 5,450 6,184 11,584 Outages Escalated 1,100 2,418 4,532
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Theft Detection
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Revenue Assurance
Theft detected during initial AMR installation Initial focus of using various meter tamper flags to detect
potential theft of service proved ineffective Cellnet & PECO developed more advanced tools looking at
irregular usage patterns combined with tamper flags• Repeated outages
• Unexplained usage
• Customer Load Profile / Irregular Load Shape
• Repetitive Flags
Analysis is used to direct Revenue Protection crews to suspect areas
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Revenue Assurance Reports
Outage & Reverse Rotation
No Weekend Usage
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Revenue Assurance Reports
Irregular Usage
No Read-Window Usage
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Examples of Customer BillsDATE USAGE DAY DAU REVENUE07/25 8720 31 281.2 901.7406/24 6667 31 215.0 777.9605/24 4911 29 169.3 544.3704/25 2646 32 82.6 349.8603/24 2716 30 90.5 366.87
DATE USAGE DAY DAU REVENUE08/12 1652 29 56.9 241.3407/14 1412 30 47.0 205.6806/14 981 32 30.6 141.6205/13 575 30 19.1 79.8904/13 335 30 11.1 48.69
DATE USAGE DAY DAU REVENUE08/17 1391 30 46.3 202.5507/18 1314 32 41.0 191.1106/16 1026 30 34.2 148.3105/17 678 32 21.1 93.2704/15 373 29 12.8 53.63
Prior to Corrections
Prior to Corrections
Prior to Corrections
After Corrections
After Corrections
After Corrections
128%
96.4%
117%
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Engineering Studies
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Load Management
The goal is to use AMR data to get a better understanding of how the distribution system is operating.
Visibility into individual distribution transformer and cable loading is created
The models are based on combination of actual customer usage, billing data, SCADA-based substation information and weather data.
4 circuits in a dense, urban environment were modeled with the Itron Distribution Asset Analysis Software
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PECO, Itron & Microsoft collaborated to conduct a demonstration of the DAA application
4 circuits in a dense, urban environment were modeled• 7,500 customers• 269 transformers
Data Sources• SCADA – 20 points input• Daily and ½ hourly meter data
Several enhancements were required to correctly model the circuits:• Virtual nodes to model Secondary Mains• Interposing, Step-Down Transformers• 2-Phase, Scott Connected Transformers
Load Management Pilot
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Transformer Utilization
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Meter to Transformer Rollup
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Transformer Profile
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Preliminary DAA Results
DAA predicted overloads on 2 of the 5 transformers that failed in summer ’06 on one of the demonstration circuits• 1 transformer failed just after midnight, customers experienced a 4
hour interruption
DAA provided secondary main loading data that was previously unavailable• Heavily loaded mains are now under analysis
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SpringGard
Interval Data Pilot
Old CityOld City
ChinatownChinatown
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Outage Prediction
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Outage Prediction
AMR Last-Gasp and Power-Up Messages • 750,000 Last-Gasps Annually, 5% associated with
actual outages• 6,000,000+ Power-Up Annually
Why? What do these messages mean?
Precursors• Demonstrated to give advance notice• Need to develop means to interpret these messages
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High Density of Power-Up Messages
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Outage Vs Power-Up Messages
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Orphan Meter Analysis
Orphan meters are read by the AMR Network, but there is no corresponding customer location information• Affected customers may receive estimated bills • New meter sets may go unbilled – lost revenue
Analysis Process:• Map AMR network elements that are ‘hearing’ orphan meters• Overlay known meter locations vs. tax parcel & vacancy data • Identify occupied tax parcels that do not have meters that are
within the range of the network device
Results are used to direct field area investigations
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Orphan Meter Analysis
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Smart Grid
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Urban Utilinet Trial
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Sample Manhole Installation
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PECO Utilinet Pilot
Demonstrate that the following devices can operate simultaneous via a single smart network:
Distribution Automation• Reclosers (Monitoring & Control)• Unit Substations (Monitoring & Control)• Faulted Circuit Indicators
Meter Reading• Current Meter Reading Functions• Remote Disconnect/Reconnect Meters• Interval Data/Demand Response• Voltage Sensing
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Jenkintown Area
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Closing Thought
There continues to be a wealth of opportunities to extract real business value from AMI, well beyond what is being delivered today.
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David Glenwright
Manager, AMR Operations & Strategies
Email: [email protected]
Phone: 215-841-6174
Contact Information