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

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

1 Overview of Full Use Guide on Electric Power Distribution Reliability Indices Panel Session – How to Define Major Events July 22, 2002 Presented by Cheryl A. Warren

2 7/22/20022 Foundations 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.

3 7/22/20023 Foundations 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….

4 7/22/20024 Foundations of the Definition Definition must be extensible. The approach must address varying levels of data collection. ØSome 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.

5 7/22/20025 Process 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.

6 7/22/20026 Summary The assembled panel will describe the proposed methodology, why one is needed, and potential benefits of the proposed approach.

7 7/22/20027 Presenters 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

8 Major Reliability Events Self - Defining? Charlie Williams, P.E. Florida Power Senior Member IEEE

9 7/22/20029 Major 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

10 7/22/ Other Major Event possibilities Severe Lightning Storm Earthquake Dust Storm Other??????

11 7/22/ Reliability 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.

12 7/22/ Suncoast 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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16 7/22/ Self Defining? Outage and Reliability statistics clearly show this event as an outlier Customer Expectations ???????

17 7/22/ New 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

18 7/22/ Statistical Analysis of Reliability Data

19 7/22/ Comparison of Event Definition vs. Statistical Definition

20 7/22/ Conclusion 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.

21 IEEE Power Engineering Society Summer Meeting Reliability Surveying Criteria David J. Schepers, IEEE Member Manager, Distribution Operating Ameren - St. Louis, MO

22 7/22/ Why New Survey Criteria? Desire to Benchmark Utility Companies Regulators Performance-Based Rates Continuous Improvement - Determine what makes a Difference Need for comparative statistics

23 7/22/ Problems with Current Surveys No Company Identification Issues of Data Accuracy Whats Included/Excluded Storms Diverse Companies Geography Data Collection Capabilities SCADA/DA Implementation AMR Outage Reporting Lack of Common Reporting Standards

24 7/22/ Major Event Definition Problem Storm-excluded indices are most valuable for benchmarking Current published IEEE definition vague Applied by 50% of respondents using 10% customers out, some >24 hours in a region (whats a region?) Need a definition that puts everyone on a common standard IEEE Working Group on System Designs new definition - Major Events

25 7/22/ The OMS And Connectivity Automated vs. Manual OMS Extent Of Connectivity Customer to transformer Transformer to protective device Protective device to upstream protective device Protective device to substation breaker Breaker to bus How many customers are really out?

26 7/22/ AMR Outage Reporting Accurate maintenance outage records Supplement phone calls for more accurate outage records Number of customers affected Outage start time

27 7/22/ Outage Definition Sustained vs. momentary Time definition (IEEE 1366: >5 minutes) Human intervention Exclusions Maintenance outages Public-caused outages Different definitions by cause by utility

28 7/22/ DA/Scada Affects CAIDI/SAIDI Opportunity to change sustained interruptions into momentary (SAIFI/MAIFI) Knowing the extent of implementation allows for better comparison

29 7/22/ System Geography Urban/Suburban/Rural Network vs. radial Urban radial (many feeder ties) vs. rural radial (few feeder ties) Circuit length issues Customer density

30 7/22/ New 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?

31 7/22/ What 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)

32 7/22/ Data 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

33 7/22/ Summary 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

34 The Need to Segment (Exclude) Abnormal Events from the Calculation of Reliability Indices Presented by Jim Bouford National Grid

35 7/22/ I. Reasons for Measuring Reliability Identification of Problems Allocation of Resources Accepted Measure of Customer Service Performance Based Ratemaking Comparison with Other Utilities

36 7/22/ II. Requirements of Measurements Comparable Year-to-Year ( Trends ) Utility-to-Utility ( Regulatory ) Universally Applicable Correlates Output to Input

37 7/22/ III. 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

38 7/22/ IV. 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

39 7/22/ V. What To Do Separate Abnormal from Normal Occurrences Review the Response to the Abnormal Occurrence Use Normal Occurrences for Measurements

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