Leveraging AMI Interval Data

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Leveraging AMI Interval Data Real Implementations in Large Scale Deployments Jack Robertson VP & GM Elster Canada Frank Fabiano Director Customer Service Horizon Utilities Corporation Steve MacDonald Manager Meter Technologies Toronto Hydro

Ontario Smart Meter Initiative Ontario is one of 10 Canadian Provinces home to 13 million Canadians (nearly 40% of all Canadians) Territory 1.5 times larger than Texas Over 50% of Canada s Manufacturing Major Energy Crunch Closing down coal plants No major generation construction underway Interconnection limitations Severe energy shortages expected

Ontario s Conservation Initiative Includes Mandated deployment of Smart Meters by 2010 in every home and business 4.5 Million meters by 2010 Hourly Interval from every meter Data must be transmitted to Provincial MDMR by 5:00 AM Data available to every customer by 8:00 AM next day

Provincial Data Architecture 90 Utilities across the Province Smart Meter Entity (SME) Government Monthly TOU Hourly interval data buckets for from billing every meter returned to sent Utility by 5:00 AM daily Provincial MDMR Access to data by service providers, retailers, etc.

Operational Data Store Utilities are finding that the Provincial MDMR will not provide the valuable data access and management that can be leveraged Utilities are implementing their own MDMRs, referred to as Operational Data Sores, or ODS

Status -OntarioSmart Meter Initiative Over 2 million meters installed so far in the Province Toronto and Horizon collecting hourly interval data from over 600,000 points Leveraging data for operations posting the data on the web for customers nightly Let s hear from their experiences

Horizon Utilities ODS Overview Frank Fabiano Director Customer Service Horizon Utilities Corporation

Smart Meter Backhaul Mass deployment currently exceeding 150,000 meters All Meters are read through wireless GPRS modems All meters are read on off hours (10:00pm 5:00am)

MAS 6.0.4 System Dashboard

Operational Data Store Overview CIS MWF OMS ODS AMCC GIS ERP SCADA

What an In House ODS can provide Stopped meter reports Meters not read reports Hourly interval data for system analysis Hourly interval data for Web Presentment Tools for Customer Service requirements Data for Engineering/Operations

Reports To Date/Using the Data Voltage reports Theft/Grow house reporting Usage on Cut for Non Pay Usage on disconnected meters Using register reads for billing purposes Using register reads for Final Bills Sync AMCC to CIS with exception reports Track meters issued from stores

Future Horizon Pilots Using ODS Outage Management Reporting Ping restored areas Load Management Auto Service Order creation Water Meters

Sample TX Load Profile (1 Hour) LOXFMR MV9ACCT MV9DATE MV9TIME MV9KWH LOMETE LOSADN LOSADD TRHAM7259 119059 02/17/2009 12:00:00 0.14 283300 15 MARLOWE DR TRHAM7259 64961 02/17/2009 12:00:00 0.62 282571 5 BURRWOOD DR TRHAM7259 71808 02/17/2009 12:00:00 0.32 282559 9 BURRWOOD DR TRHAM7259 106473 02/17/2009 12:00:00 0.39 282557 15 BURRWOOD DR TRHAM7259 122967 02/17/2009 12:00:00 0.67 282556 19 BURRWOOD DR TRHAM7259 24445 02/17/2009 12:00:00 1.08 282570 20 BURRWOOD DR TRHAM7259 140318 02/17/2009 12:00:00 0.56 282558 23 BURRWOOD DR TRHAM7259 142978 02/17/2009 12:00:00 0.95 282568 24 BURRWOOD DR TRHAM7259 46191 02/17/2009 12:00:00 1.17 282550 27 BURRWOOD DR TRHAM7259 96490 02/17/2009 12:00:00 0.45 282569 28 BURRWOOD DR TRHAM7259 665861 02/17/2009 12:00:00 0.68 282549 31 BURRWOOD DR TRHAM7259 813815 02/17/2009 12:00:00 0.6 282565 32 BURRWOOD DR TRHAM7259 82468 02/17/2009 12:00:00 0.54 282548 35 BURRWOOD DR TRHAM7259 34472 02/17/2009 12:00:00 0.42 282567 36 BURRWOOD DR TRHAM7259 134586 02/17/2009 12:00:00 0.31 282551 39 BURRWOOD DR TRHAM7259 8162 02/17/2009 12:00:00 0.44 294948 40 BURRWOOD DR TRHAM7259 122933 02/17/2009 12:00:00 4.06 370573 16 BURRWOOD DR Total Load 13.4

Identifying nontechnical losses Compare Distribution Transformer Load with the summation of downstream loads by adding a meter at the transformer

Grow-House Meter Read Illegal Use of Pow er Graph 0 1 2 3 4 5 6 7 8 9 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 Date & Time kwh's/hour kwh's

Toronto Hydro at a Glance Steve MacDonald Manager Meter Technologies Toronto Hydro Revenue $2.3 Billion (Canadian) Customers 678,000 Residential & Commercial 250,000 Apartment & Condominium Units Population 2.5 Million Peak Load 5,000 MW Employees 1,700 Affiliate Businesses Electricity Distribution Energy Services 18

Smart Meter Architecture 19

Time of Use Pricing The Summer Weekdays Summer Winter Hi On Peak- High Price Mid Peak- Mid Price Off Peak- Low Price 20

Web Pilot Presents TOU data online for each customer- LIVE DEMO 21

Web Pilot Results 90% of pilot group found the web easy to use 80% would go to the Toronto Hydro website first before contacting the Call Center Virtually all customers are aware of Smart Meters, how they work and the ability to review electricity online Customers are more likely to visit the site to better understand their electricity use than to learn about conservation Almost two-thirds of customers visit the web site at least once a month 22

Customer Impact TOU- shift consumption to off peak times Customer understands consumption patterns Supports conservation programs 23

Questions? Frank Fabiano Steve MacDonald Jack Robertson