Published by

- John D. Kueck and Brendan J. Kirby, Oak Ridge National Laboratory
- Philip N. Overholt, U.S. Department of Energy
- Lawrence C. Markel, Sentech, Inc.

*Published in Measurement Practices for Reliability and Power Quality: A Toolkit of Reliability Measurement Practices, 2004*

*Prepared by Oak Ridge National Laboratory Oak Ridge, Tennessee 37831-6285 managed by UT-BATTELLE, LLC for the U.S. Department of Energy under contract DE-AC05-00OR22725*

Because some utilities are adopting performance-based rates, the importance of calculating reliability indices is growing. In order to do an “apples-to-apples” comparison between utilities, it is essential that reliability index calculation and reporting methods be uniform. A nationwide survey of information used for calculating distribution reliability indices was recently performed.^{4} The survey found a number of different sources of disparity between utility practices. Some of the most significant issues are summarized as follows.

One significant source of discrepancies is step restoration. When a utility takes actions to restore power after a large-scale outage, the restoration proceeds in steps. If customer minutes are not tracked accurately as these steps are taken, the “start” and “end” times of the interruption can increase or decrease and have a major impact on the calculated indices.

How far down does the utility go in analyzing an interruption? Does the analysis go to the distribution substation, circuit breaker, recloser, sectionalizer, fuse, transformer, service, or meter? Survey results have shown that the system average interruption duration index (SAIDI) can double with the inclusion of data down to the fuse level. Some utilities calculate SAIDI only down to the substation level.

The momentary average interruption frequency index (MAIFI), which is the total number of customer momentary interruption events divided by the total number of customers served, measures data on “momentary” interruptions that result in a zero voltage. For example, two circuit breaker open operations equals two momentary interruptions. Another index, the system average interruption frequency index (SAIFI), is the total number of customer interruptions divided by the total number of customers served. Some utilities include MAIFI data in the SAIFI calculation. When MAIFI data is included in the SAIFI calculations, the SAIFI index can triple. In addition, obtaining the momentary information accurately is sometimes quite difficult because some reclosers and distribution breakers are not equipped with SCADA.

A “major event” is defined in IEEE Standard 1366 as a catastrophic event that exceeds the design limits of the power system. Utilities are permitted to exclude major events when calculating their indices. There is a wide variance, however, in how a major event is defined in practice and how it is used for excluding abnormal data. Some utilities use a major event definition that is set by the governing regulatory agency; others use their own definition. This has a tremendous impact on the calculated indices. Of the surveyed utilities, 70% said that they had a major event definition, and 53% said that their major event definition was the same as that used by the governing regulatory agency.

Finally, how data are entered has a bearing on validity. Some utilities have a computer-based system for calculating indices in which interruption data are automatically entered, while others enter data manually through a spreadsheet-based system. It was found that the more sophisticated the computerized system is, the more likely it is that the data will be consistent and reflect actual system performance.

In addition, there was a feeling expressed among the survey respondents that generation and transmission should have their own reliability indices, and that these should not be included in the calculation of distribution reliability. One utility found that including transmission and generation interruptions increases SAIDI by 131% and SAIFI by 120%.

It is clear that the process used for calculating reliability indices can vary greatly from utility to utility. The input data sources vary tremendously, and there are major differences in basic calculation methods. The indices are essentially useless for comparing utility performance unless these discrepancies are identified and understood. When applied consistently, the indices are useful for examining year-to-year trends within a specific utility, but when comparing utilities with different data collection methods and definitions, as described above, the indices presently can be quite misleading.

**Reference**

4. *C. A. Warren, “A Nationwide Survey of Recorded Information Used for Calculating Distribution Reliability Indices,” IEEE Transactions on Power Delivery 18, no. 2 (April 2003).*