McGranaghan US Session 2 Block 4 Question 12 Barcelona 12-15 May 2003 1 Statistical Framework for...

1McGranaghan US Session 2 Block 4 Question 12

Barcelona 12-15 May 2003

Statistical Framework for Establishing Target Reliability Levels

and Classifying Major Event Days

Mark McGranaghanEPRI PEAC Corporation

[email protected]



Background• Deregulation and, in some instances, re-regulation have caused a

renewed interest in distribution reliability

• Several issues are leading to increased regulatory scrutiny of distribution reliability:

– Emerging trend of decoupling price/revenue from cost of distribution service for a certain period of time (“regulatory period”) which allows regulated entities to earn higher profit by reducing cost

– Concern regarding excessive budget cutting in the “wires” business to recover huge losses experienced in the energy trading and other businesses

– Perception of decreased reliability during severe weather events

• In December 2002, EPRI PDM initiated a project to review the current situation in distribution reliability performance indicators for utilities in United States



Characterizing Reliability

• Most common indices (IEEE P1366) – SAIFI, SAIDI

• Statistical variations are critical

• Target levels must include control ranges based on statistical variation characteristics

• Handling of “Major Event Days” is a critical factor



Statistical Methods

• Characterize variability of reliability indices

• Establish control regions

• Performance-based rates



Defining Major Events

• “Major Event” is defined as an event (typically weather related) that exceeds reasonable design and or operational limits of the electric power system

• Widespread service interruption during a major event can significantly influence the yearly distribution reliability indices

• Inconsistencies in the definition of “Major Events” has been a bottleneck in comparing reliability statistics among different utilities

• IEEE is proposing a statistically-based definition of “Major Event” as part of IEEE P1366 Draft Full-Use Guide for Electric Power Distribution Reliability Indices



Impact of Major Events on SAIDIIncrease in SAIDI Values for Utilities That Reports Indices With

Major Events Included and Excluded

0%

200%

400%

600%

800%

1000%

1200%

1400%

1992(9)

1993(10)

1994(10)

1995(10)

1996(9)

1997(13)

1998(13)

1999(12)

2000(10)

2001(10)

Year (# of Utilities Reporting)

% In

crea

se in

SA

IDI

1

SAIDI (Maximum)

SAIDI (Average)



Increase in SAIFI Values for Utilities That Reports Indices WithMajor Events Included and Excluded

0%

20%

40%

60%

80%

100%

120%

1992(9)

1993(10)

1994(10)

1995(10)

1996(9)

1997(13)

1998(13)

1999(12)

2000(10)

2001(10)

Year (# of Utilities Reporting)

% In

crea

se in

SA

IFI

1

SAIFI (Maximum)

SAIFI (Average)

Impact of Major Events on SAIFI



Pitfalls in Comparing Reliability Performance

• Definition & Data Classification– Major Events– Planned vs Unplanned Events– Momentary interruptions vs outages– Distribution/Transmission

• Service Territory– Geography, weather, vegetation, animals, load density

• Data Collection Process– Monitoring vs other methods of data collection

• System Design– Overhead vs underground, voltage levels, networks, protection,

etc.



Comparing Utility Reliability Indices

• Consistency in definition of reliability indices and

accountability of major events through standardization will

promote uniformity among utilities

• Need uniformity on an international basis

• Collaborative project to compare methods for

characterizing reliability, identify preferred statistical

methods, benchmark with actual data

McGranaghan US Session 2 Block 4 Question 12 Barcelona 12-15 May 2003 1 Statistical Framework for...

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