Overview of 1366-2001 Full Use Guide on Electric Power Distribution Reliability Indices Panel Session – How to Define Major Events July 22, 2002 Presented.

Overview of 1366-2001 Overview of 1366-2001 Full Use Guide on Electric Power Full Use Guide on Electric Power

Distribution Reliability IndicesDistribution Reliability Indices

Panel Session – How to Define Major EventsJuly 22, 2002

Presented by Cheryl A. Warren

7/22/2002

2

Foundations of the DefinitionFoundations of the Definition

• Purpose is to partition the data into normal and abnormal days.

• Rigorously analyze and report on abnormal events above and beyond the normal process.

• Use normal events for trending, internal goal setting, and Commission mandated targets.

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Foundations of the DefinitionFoundations of the Definition

• Definition must be understandable by all and easy to apply.Executives and Commissioners must be able to

understand and feel comfortable with the approach.

• Definition must be specific and calculated using the same process for all utilities.

• Must be fair to all utilities.Large and small, urban and rural….

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Foundations of the DefinitionFoundations of the Definition

• Definition must be extensible.The approach must address varying levels

of data collection.Some utilities have little reliability data. Others

have been collecting it with flawed system. Others have very sophisticated systems that track interruptions to the customer level.

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Process To DateProcess To Date

• Members agreed that the current definition should be reevaluated.

• A subgroup was formed to further analyze approaches. Jim Bouford , Rich Christie, Dan Kowaleski, John

McDaniel, Dave Schepers, Cheri Warren, Charlie Williams & Joe Viglietta

• Members discussed the options and performed analysis using real data.

• This panel session will share some of the background behind the current thinking.

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SummarySummary

• The assembled panel will describe the proposed methodology, why one is needed, and potential benefits of the proposed

approach.

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PresentersPresenters

• Rich Christie University of Washington

• Charlie Williams Florida Power Corp A Progress Energy Company

• Dan Kowalewski Exelon – ComEd

• Dave Schepers Ameren Energy

• Jim Bouford National Grid

Major Reliability EventsMajor Reliability EventsSelf - Defining?Self - Defining?

Charlie Williams, P.E.Florida Power

Senior Member IEEE

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Major Event DefinitionsMajor Event Definitions

• P1366 (old)- 10% of customers in a 24 hour period

• Regulatory Agencies - Severe Storms (Hurricane, Ice Storm, Tornado, Other)

• P1366 (new) - statistical outlier definition

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Other Major Event possibilitiesOther Major Event possibilities

• Severe Lightning Storm

• Earthquake

• Dust Storm

• Other??????

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Reliability AccountabilityReliability Accountability

• Some events are severe - power systems cannot be reasonably or economically designed to withstand them.

• What kind of events should the utility design consider?

• With PBR these issues take on a potential economic impact to the utility and shareholders as well as rate payers.

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Suncoast Lightning StormSuncoast Lightning Storm

• Major Event not defined as severe.

• No definition of severe lightning by NWS

• Lightning data shows it as a “once in 10 year event”.

• Outside help required to assist with restoration

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Suncoast Average Daily Flash Count - July

399 25836

338 339 242 148354 166 367

5813

0

1000

2000

3000

4000

5000

6000

7000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 36722

Year

Avg

DA

ily

Fla

sh C

ou

nt

(Ju

ly) Ten year daily average July flashes =

2657/15/00 = 22 times greater than ten year average

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Suncoast RegionWorst Outage Days

219238

217

166

111

177162

216

260

159

422

0

50

100

150

200

250

300

350

400

450

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 36722

Year

Max

imu

m D

aily

Ou

tag

e C

ou

nt

Average Worst Outage Day (all months) = 1927/15/00 = 2.2 times greater than annual average worst day

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Suncoast Daily Regional SAIDI

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

01/0

1/93

05/0

1/93

09/0

1/93

01/0

1/94

05/0

1/94

09/0

1/94

01/0

1/95

05/0

1/95

09/0

1/95

01/0

1/96

05/0

1/96

09/0

1/96

01/0

1/97

05/0

1/97

09/0

1/97

01/0

1/98

05/0

1/98

09/0

1/98

01/0

1/99

05/0

1/99

09/0

1/99

01/0

1/00

05/0

1/00

09/0

1/00

01/0

1/01

05/0

1/01

09/0

1/01

Date

SA

IDI

Suncoast StormSAIDI = 7.1

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Self Defining?Self Defining?

• Outage and Reliability statistics clearly show this event as an “outlier”

• Customer Expectations ???????

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New Major Event DefinitionNew Major Event Definition

• Statistical process to establish “normal” reliability parameters for daily outage statistics based on historical data

• Establish limits for major events

• Review these limits annually

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Statistical Analysis of Reliability Data

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Severe vs Non-Severe WeatherSuncoast Region

0

10,000,000

20,000,000

30,000,000

40,000,000

50,000,000

60,000,000

70,000,000

80,000,000

90,000,000

100,000,000

0 100 200 300 400 500 600 700 800 900 1000

# Daily Outages

Dai

ly C

MI

NON-SEVERE

Severe

Suncoast Storm 7/15/2000

3/13/93

3/14/93

9/17/2000

4/25/91

Comparison of Event Definition vs. Statistical Definition

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ConclusionConclusion

• Statistical Definition is definitive and non-ambiguous

• Leaves little room for debate on major events.

• Only excludes events that are of significant impact to the system.

IEEE IEEE Power Engineering Society Power Engineering Society

Summer MeetingSummer Meeting

Reliability Surveying Criteria

David J. Schepers, IEEE MemberManager, Distribution Operating

Ameren - St. Louis, MO

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Why New Survey Criteria?Why New Survey Criteria?

• Desire to BenchmarkUtility CompaniesRegulators

• Performance-Based Rates

• Continuous Improvement - Determine what makes a Difference

• Need for comparative statistics

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Problems with Current SurveysProblems with Current Surveys

• No Company Identification

• Issues of Data Accuracy What’s Included/Excluded Storms

• Diverse Companies Geography Data Collection Capabilities SCADA/DA Implementation AMR Outage Reporting

• Lack of Common Reporting Standards

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Major Event Definition ProblemMajor Event Definition Problem

• Storm-excluded indices are most valuable for benchmarking

• Current published IEEE definition vagueApplied by 50% of respondents using 10%

customers out, some >24 hours in a region (what’s a region?)

• Need a definition that puts everyone on a common standard

• IEEE Working Group on System Designs new definition - Major Events

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The OMS And ConnectivityThe OMS And Connectivity

• Automated vs. Manual OMS• Extent Of Connectivity

Customer to transformerTransformer to protective deviceProtective device to upstream protective deviceProtective device to substation breakerBreaker to bus

• How many customers are really out?

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AMR Outage ReportingAMR Outage Reporting

• Accurate maintenance outage records

• Supplement phone calls for more accurate outage recordsNumber of customers affectedOutage start time

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Outage DefinitionOutage Definition

• Sustained vs. momentaryTime definition (IEEE 1366: >5 minutes)Human intervention

• ExclusionsMaintenance outagesPublic-caused outagesDifferent definitions by cause by utility

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DA/ScadaDA/Scada

• Affects CAIDI/SAIDI

• Opportunity to change sustained interruptions into momentary (SAIFI/MAIFI)

• Knowing the extent of implementation allows for better comparison

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System GeographySystem Geography

• Urban/Suburban/Rural

• Network vs. radial

• Urban radial (many feeder ties) vs. rural radial (few feeder ties)

• Circuit length issues

• Customer density

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New Questions In EEI SurveyNew Questions In EEI Survey

• Do you have an automated OMS with Full Connectivity?

• Percentage of Customers with AMR Outage Reporting• Percentage of Customers served by SCADA

Substations• Percentage of Customers on Distribution Circuits with

Automated Switching• Urban/Suburban/Rural Geography• Does your OMS have Partial Restoration Capability?• Will your utility identify itself for others willing to do

likewise?

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What to Report to EEIWhat to Report to EEI

• Standard IEEE Indices SAIFI, CAIDI, SAIDI, MAIFI

• Percentage of Interruptions and Hours by Cause, by System Location

• Actual & Normalized for Major Events

• Percentage of Customers with 0, 1, 2, 3, 4, 5 or more Normalized Interruptions (CEMI)

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Data and Indices DefinitionsData and Indices Definitions

• Use IEEE 1366 Definitions for Standard Indices

• Sustained Interruptions >5 minutes

• No outage types excluded other than Customer Outage caused by Customer Equipment

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SummarySummary

• Need exists for benchmarking for utilities and regulators alike

• Current surveys do not allow for accurate comparisons

• More segmentation is needed and possible

• EEI Reliability Survey is moving in this direction today

The Need to Segment The Need to Segment (Exclude) Abnormal Events (Exclude) Abnormal Events

from the Calculation of from the Calculation of Reliability IndicesReliability Indices

Presented by Jim Bouford National Grid

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I. Reasons for Measuring ReliabilityI. Reasons for Measuring Reliability

• Identification of Problems

• Allocation of Resources

• Accepted Measure of Customer Service

• Performance Based Ratemaking

• Comparison with Other Utilities

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II. Requirements of MeasurementsII. Requirements of Measurements

• ComparableYear-to-Year ( Trends )Utility-to-Utility ( Regulatory )

• Universally Applicable

• Correlates Output to Input

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III. Design and Operation RealitiesIII. Design and Operation Realities

• Systems are NOT built to withstand all contingencies

• Workforce levels are set to handle routine activities

• Systems are designed and operated to deal with a defined level of adverse occurrences

• Abnormal occurrences stress the design and/or the operation of the system and Require Abnormal Operational Response

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IV. Simple TruthsIV. Simple Truths

• Expected Occurrences only Require Normal Response

• Abnormal Occurrences Require Abnormal Response

• Abnormal Occurrences Will Distort the Measures; Requirements of Measurement Will Not be Met

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V.V. What To Do What To Do

• Separate Abnormal from Normal Occurrences

• Review the Response to the Abnormal Occurrence

• Use Normal Occurrences for Measurements