5.4 ERMUSR 05-11-2021______________________________________________________________________________
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UTILITIES COMMISSION MEETING
TO:
ERMU Commission
FROM:
Mike Tietz –Technical Services Superintendent
MEETING DATE:
May 11, 2021
AGENDA ITEM NUMBER:
5.4
SUBJECT:
2020 Annual Reliability Report
ACTION REQUESTED:
Receive the APPA eReliability Tracker 2020 Annual Benchmarking Report for ERMU
BACKGROUND:
Minnesota Rules Chapter 7826 Public Utilities Commission Electric Utility Standards cover
safety, reliability, service, and reporting requirements. Per 7826.0100(A), municipal utilities are
exempt from these requirements. However, the Elk River Municipal Utilities Commission
adopted several parts of this chapter as a Distribution Reliability Standard policy requiring
annual reporting on system reliability.
DISCUSSION:
In 2020, our reliability index numbers remain very good. These reliability index numbers reflect
the condition of our robust electrical system as well as the superb response time from our local
line crews. This also reflects the local accountability, long term visioning on system design, and
ongoing system maintenance. The table below reflects the number of customer outage
minutes for the last 10 years.
Year # of Customers # of Outage Minutes # of Outages
2011 9576 297,359 51
2012 9285 71,496 57
2013 9285 55,451 31
2014 9426 243,965 44
2015 9449 225,337 41
2016 10862 432,310 59
2017 11489 354,625 40
2018 12158 117,055 51
2019 12463 312,885* 58
2020 12604 197,884 51
*118,978 of these minutes are due to two separate transmission outages.
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Listed below are a number of reliability indices that are used by the electric industry to make it
easier to compare performance among utilities along with ERMU’s 2019 and 2020 statistics.
Average Service Availability Index (ASAI)
ASAI is a measure of the average availability of the sub-transmission and distribution systems
to serve customers. It is the ratio of the total customer minutes that service was available to
the total customer minutes available in a time period. This is normally expressed as a
percentage.
ERMU’s 2020 ASAI is 99.9969% Availability ERMU’s 2019 ASAI is 99.9951% Availability
Customer Average Interruption Duration Index (CAIDI)
CAIDI is defined as the average duration (in minutes) of an interruption experienced by
customers during a specific time frame. It is calculated by summing the customer minutes off
during each sustained¹ interruption in the time period and dividing this by the number of
customers experiencing one or more sustained¹ interruptions during the time period. The
resulting unit is minutes. The index enables utilities to report the average duration of a
customer outage for those customers affected.
ERMU’s 2020 CAIDI is 99.689 minutes ERMU’s 2019 CAIDI is 60.111 minutes
System Average Interruption Duration Index (SAIDI)
SAIDI is defined as the average interruption duration (in minutes) for customers served
during a specified time period. It is determined by summing the customer minutes off for each
sustained¹ interruption during a specified time period and dividing that sum by the average
number of customers served during that period. The resulting unit is minutes. This index
enables the utility to report how many minutes’ customers would have been out of service if all
customers were out at one time.
ERMU’s 2020 SAIDI is 15.795 minutes ERMU’s 2019 SAIDI was 25.412 minutes
System Average Interruption Frequency Index (SAIFI)
SAIFI is defined as the average number of times that a customer is interrupted during a
specified time period. It is determined by dividing the total number of sustained¹ interrupted
customers in a time period by the average number of customers served. The resulting unit is
“interruptions per customer.”
ERMU’s 2020 SAIFI is 0.158 ERMU’s 2019 SAIFI was 0.423
¹ Only outages lasting longer than five minutes are included in the calculations, as defined by IEEE 1366.
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Staff reviews these statistics in detail to find ways to continually improve our system. These
statistics are very good compared to other utilities. As indicated by the following pie chart and
statistics list, you can see the cause of the outages that we experienced in 2020.
Many investor owned and cooperative run utilities “storm normalize “ their reliability numbers
by removing “major outages” due to storms from their reliability index number calculations.
Our reliability numbers have not been storm normalized. Our numbers reflect these major
outages and represent what our customers experienced in 2020. Overall, our electric
distribution system is robust, and our system reliability is very high.
Attached is the American Public Power Association’s (APPA) eReliability Annual Report for Elk
River Municipal Utilities which contains published averages that can be used to better
understand the performance of our electric system relative to other utilities nationally and to
those within their region or size class.
ATTACHMENT:
• APPA eReliability Tracker 2020 Annual Report for Elk River Municipal Utilities
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Elk River Municipal Utilities
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I. About this Report
This report focuses on distribution system reliability across the country and is customized
to each utility that participates in the American Public Power Association’s eReliability
Tracker service. APPA created the eReliability Tracker Annual Report to assist utilities in
their efforts to understand and analyze their electric system. In 2012, APPA developed the
eReliability Tracker thanks to a grant from the Demonstration of Energy & Efficiency
Developments (DEED) program.
This report reflects data in the eReliability Tracker from January 1, 2020 to December 31,
2020. If you do not have a full year of data in the system, then this analysis might not
properly reflect your utility's statistics. The report only includes data recorded as of
February 7, 2021. Reliability reflects both historic and ongoing engineering investment
decisions within a utility. Proper use of reliability metrics ensures that a utility is
performing its intended function and is providing service in a consistent and effective
manner.
While the primary use of reliability statistics is for self-evaluation, you can use these
statistics to compare your utility with similar utilities. However, differences such as
electrical network configuration, ambient environment, weather conditions, and number
of customers served typically limit most utility-to-utility comparisons. Due to the diverse
range of utilities that use the eReliability Tracker, this report endeavors to improve
comparative analyses by grouping utilities by size and region.
Since this report contains data for all utilities that use the eReliability Tracker, it is
important to consider how a particularly large or small utility can affect the rest of the
data. To ease the issues associated with comparability, each utility’s reliability statistics
are weighted based on customer count when aggregated. This means that all utilities are
equally weighted and all individual statistics are developed on a per customer basis.
The aggregate statistics displayed in this report are calculated from 271 utilities that
verified their 2020 outage data. Utilities that experienced no outages in 2020, or did not
upload any data, will have NULL, nan, or "0" values in their report for utility-specific data
and were not included in the aggregate analysis. Also note that log-normal data with a z-
score greater than 3.25 will be considered for inclusion and may be excluded if it
significantly distorts the aggregate statisitics.
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Utility Classifications
This report separates utilities into groups according to geographic region and the number
of customers served. Table 1 shows the range of customer sizes for utilities that use the
eReliability Tracker by five distinct customer size class groups of approximately 100
utilities per group.
Your utility belongs to customer size class 4 and region 3.
Table 1. Customer size range per customer size class
Customer Size Class Customer Size Range
Class 1 [0, 1508)
Class 2 [1508, 3202)
Class 3 [3202, 6996)
Class 4 [6996, 13497)
Class 5 [13497, 468522)
Each utility is also grouped with all other participating utilities within their region. Figure 1
shows the number of utilities using the eReliability Tracker in each region and Figure 2
shows the states and territories included in each region.
Figure 1. Number of utilities subscribed to the eReliability Tracker by region
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Figure 2. Regions
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II. IEEE Statistics
When it comes to reliability metrics, the industry standard metrics are defined in the
Institute for Electrical and Electronics Engineers’ Guide for Electric Power Distribution
Reliability Indices, or IEEE 1366 guidelines. For each utility, the eReliability Tracker
performs IEEE 1366 calculations for System Average Interruption Duration Index (SAIDI),
System Average Interruption Frequency Index (SAIFI), Customer Average Interruption
Duration Index (CAIDI), Momentary Average Interruption Frequency Index (MAIFI) and
Average Service Availability Index (ASAI).
It is important to note how major events (MEs) are calculated and used in this report. An
example of a ME includes severe weather, such as a tornado or hurricane, that leads to
unusually long outages in comparison to your distribution system’s typical outage. Both
the eReliability Tracker and this report use APPA’s ME threshold, which is a calculation
based directly on the SAIDI for specific outage events, rather than daily SAIDI. APPA’s ME
threshold allows a utility to remove outages that exceed the IEEE 2.5 beta threshold for
outage events, which take up to 10 years of the utility's outage history. In the eReliability
Tracker, if a utility does not have at least 36 outage events prior to the year being
analyzed, then no threshold is calculated. If this is the case for your utility, then you will
have a NULL value in the field below and the calculations without MEs in the SAIDI section
of this report will be the same as the calculations with MEs for your utility. More outage
history will provide a better threshold for your utility.
Your utility's APPA major event threshold is 8.35.
For each of the reliability indices, this report displays your utility’s metrics alongside other
comparative groups. The first table within each of the following subsections allows you to
better understand the performance of your electric system relative to other utilities
nationwide and to those within your same region or size class. The second table breaks
down the national data into quartile ranges, a minimum value, and a maximum value.
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II.1. System Average Interruption Duration Index (SAIDI)
SAIDI is defined as the average interruption duration (in minutes) for customers served
by the utility during a specific time frame.
Since SAIDI is a sustained interruption index, only outages lasting longer than five
minutes are included in the calculations. SAIDI is calculated by dividing the sum of all
customer minutes of interruption [1] within the specified time frame by the average
number of customers served during that period. For example, a utility with 100 customer
minutes of interruption and 100 customers would have a SAIDI of 1.
Indices are calculated for outages with and without MEs; furthermore, the data are broken
down to show calculations for scheduled and unscheduled outages.
Note that in the tables below, scheduled and unscheduled calculations include MEs. Also
note that wherever MEs are excluded, the exclusion is based on APPA’s ME threshold.
Table 2. Average SAIDI with and without MEs in minutes
All No MEs Unscheduled Scheduled
Your utility 15.8 15.8 15.55 0.24
Utilities that use the eReliability Tracker 139.16 56.12 133.67 8.66
Utilities in your region 42.04 31.67 40.67 1.92
Utilities in your customer size class 90.63 36.45 87.85 4.08
Table 3. Summary SAIDI data from the eReliability Tracker
All No MEs Unscheduled Scheduled
Minimum Value 0 0 0 0
First Quartile 22.46 10.52 19.34 0.16
Median Value 54.65 28.44 48.72 0.91
Third Quartile 119.57 65.5 113.09 4.38
Maximum Value 5782.38 1065.42 5779.68 420
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Figure 3. Average SAIDI for all utilities that use the eReliability Tracker by region
1. Customer minutes of interruption is calculated by multiplying total customers interrupted and total minutes
of interruption. ↩
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II.2. System Average Interruption Frequency Index (SAIFI)
SAIFI is defined as the average number of instances a customer on the utility system will
experience an interruption during a specific period.
Since SAIFI is a sustained interruption index, only outages lasting longer than five
minutes are included in the calculations. SAIFI is calculated by dividing the total number
of customer interruptions by the average number of customers served during that period.
For example, a utility with 150 customer interruptions and 200 customers would have a
SAIFI of 0.75 interruptions per customer.
Table 4. Average SAIFI (with MEs)
SAIFI (interruptions)
Your utility 0.16
Utilities that use the eReliability Tracker 0.86
Utilities in your region 0.57
Utilities in your customer size class 0.77
Table 5. Summary SAIFI data from the eReliability Tracker
SAIFI (interruptions)
Minimum Value 0
First Quartile 0.27
Median Value 0.57
Third Quartile 1.19
Maximum Value 6.24
Figure 4. Average SAIFI for all utilities that use the eReliability Tracker by region
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II.3. Customer Average Interruption Duration Index (CAIDI)
CAIDI is defined as the average duration (in minutes) of an interruption experienced by
customers during a specific time frame.
Since CAIDI is a sustained interruption index, only outages lasting longer than five
minutes are included in the calculations. CAIDI is calculated by dividing the sum of all
customer minutes of interruption by the number of customers that experienced one or
more interruptions during that period. This metric reflects the average customer
experience (minutes of duration) during an outage.
Table 6. Average CAIDI (with MEs)
CAIDI (minutes)
Your utility 99.69
Utilities that use the eReliability Tracker 143.52
Utilities in your region 81.24
Utilities in your customer size class 116.27
Table 7. Summary CAIDI data from the eReliability Tracker
CAIDI (minutes)
Minimum Value 0
First Quartile 63.12
Median Value 88.53
Third Quartile 126.33
Maximum Value 3240.91
Figure 5. Average CAIDI for all utilities that use the eReliability Tracker by region
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II.4. Momentary Average Interruption Frequency Index (MAIFI)
MAIFI is defined as the average number of times a customer on the utility system will
experience a momentary interruption.
In this report, an outage with a duration of five minutes or less is classified as momentary.
MAIFI is calculated by dividing the total number of momentary customer interruptions by
the total number of customers served by the utility. For example, a utility with 20
momentary customer interruptions and 100 customers would have a MAIFI of 0.20.
Momentary outages can be more difficult to track and smaller utilities might not have the
technology to do so; therefore, some utilities have a MAIFI of zero.
Table 8. Average MAIFI
MAIFI (interruptions)
Your utility NULL
Utilities that use the eReliability Tracker 0.6
Utilities in your region 0.72
Utilities in your customer size class 0.4
Table 9. Summary MAIFI data from the eReliability Tracker
MAIFI (interruptions)
Minimum Value 0
First Quartile 0.02
Median Value 0.12
Third Quartile 0.48
Maximum Value 9.03
Figure 6. Average MAIFI for all utilities that use the eReliability Tracker by region
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II.5. Average Service Availability Index (ASAI)
ASAI is a measure of the average availability of the sub-transmission and distribution
systems that serve customers.
This load-based index represents the percentage availability of electric service to
customers within the period analyzed. It is calculated by dividing the total hours in which
service is available to customers by the total hours that service is demanded by the
customers. For example, an ASAI of 99.99% means that electric service was available for
99.99% of the time during the given period.
Table 10. Average ASAI (with MEs)
ASAI (%)
Your utility 99.997
Utilities that use the eReliability Tracker 99.9747
Utilities in your region 99.9921
Utilities in your customer size class 99.9828
Table 11. Summary ASAI data from the eReliability Tracker
ASAI (%)
Minimum Value 99.0085
First Quartile 99.9779
Median Value 99.9903
Third Quartile 99.9958
Maximum Value 100
Figure 7. Average ASAI for all utilities that use the eReliability Tracker by region
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II.6.Energy Information Administration (EIA) Form 861 Data
Form EIA-861 collects annual information on electric power industry participants involved
in the generation, transmission, distribution, and sale of electric energy in the United
States and its territories.
In 2014, EIA began publishing reliability statistics in Form EIA-861; therefore, APPA
included these statistics in this report for informational purposes. Please note that the
following data includes 176 investor-owned, 572 rural cooperative, and 437 public power
utilities that were large enough to be required to fill out the full EIA-861 form, and does
not include utilities that completed the EIA 861-S form (for smaller entities). Note that the
437 participating public power utilities include entities classified by EIA as municipal,
political subdivision, and state. In addition, since the collection and release of EIA form
data lags by a year, the data provided here is based on 2019 data that was published
October 6, 2020. Therefore, we suggest you only use the aggregate statistics contained
herein as an informational tool for further comparison of reliability statistics.
In Table 12 and Table 13, an entity calculates SAIDI, SAIFI, and determines major eventME
days in accordance with the IEEE 1366-2003 or IEEE 1366-2012 standard.
Although EIA collected other reliability-related data, the tables below only include SAIDI
and SAIFI data. You can download the full set of data at:
http://www.eia.gov/electricity/data/eia861/
Table 12. Summary SAIDI data from Form EIA-861, 2019
All No MEs
Average 267.07 138.78
Minimum Value 0.66 0.66
First Quartile 84.96 55.8
Median Value 164.16 99.85
Third Quartile 323.2 170.16
Maximum Value 4150 1239.3
Table 13. Summary SAIFI data from Form EIA-861, 2019
All No MEs
Average 1.65 1.26
Minimum Value 0.01 0.01
First Quartile 0.89 0.66
Median Value 1.38 1.06
Third Quartile 2.11 1.61
Maximum Value 16.45 12.39
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II.7. Analysis of Miles of Line and Interruptions
Analyzing metrics on interruptions by miles of line can help utilities explore the
relationship between outages, line exposure, and customer density. This analysis
separates utilities into groups of similar average customer density (customers served per
mile). As seen in Table 15, utilities that use the eReliability Tracker were split into five
customer density groups of approximately 79 utilities each. Note that customer density
classes include utilities that either provided their miles of line data to S&P Global Platts or
recorded their data in the eReliability Tracker. By using the miles of line-related metrics
shown in Table 14 and Table 15, you can benchmark your utility’s reliability against
system characteristics along with the customer normalized metrics included in the rest of
the report. These system topography-related metrics can be helpful in understanding, for
example, utility reliability against weather and animal-related outages relative to similarly
dense and exposed utilities.
Your utility's total miles of line: 315.0
Your utility's overhead miles of line: 95.0
Your utility's underground miles of line: 220.0
Table 14. Total miles of line and interruptions
Customers
Interrupted per Mile
Interruptions
per Mile
Minutes of
Interruption per Mile
Your utility 6 1 18.47
Utilities that use the
eReliability Tracker 245 3 522.39
Utilities in your region 463 4 522.98
Your utility's average customer density (customers per mile): 40
Your utility's belongs to customer density class 2.
Table 15. Total miles of line analysis by customer density class
Customer Density
Class (Customers per
Mile)
Customer
Density
Range
Customers
Interrupted
per Mile
Interruptions
per Mile
Minutes of
Interruption
per Mile
Class 1 0 - 30 21 1 68.02
Class 2 30 - 46 35 1 135.24
Class 3 46 - 63 38 1 669.32
Class 4 63 - 90 61 1 81.18
Class 5 90 - 13200 1121 11 1680.84
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III. Outage Causes
Equipment failure, extreme weather events, wildlife, and vegetation are some of the most
common causes of electric system outages. However, certain factors, such as regional
weather and animal/vegetation patterns, can make some causes more prevalent for a
specific group of utilities. The following section of this report includes graphs depicting
common causes of outages for your utility, all utilities in your region, and all utilities using
the eReliability Tracker.
Charts containing aggregate information are customer-weighted to account for
differences in utility size for a better analytical comparison. For example, a particularly
large utility may have a large number of outages compared to a small utility. To avoid
skewing the data toward large utilities, the number of cause occurrences is divided by
customer size to account for the differences. In Figures 8-13, the data represent the
number of occurrences for each group of 1,000 customers. A customer-weighted
occurrence rate of "1" means one outage from that outage cause occurred per 1,000
customers on average in 2020.
Note that the sustained outage cause analysis is more comprehensive than the
momentary outage cause analysis due to a bigger and more robust sample size for
sustained outages. Regardless, tracking both sustained and momentary outages helps
utilities understand and reduce outages. To successfully use the outage information
tracked by your utility, it is imperative to classify and record outages in detail. The more
information provided per outage, the more conclusive and practical your analyses will be.
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III.1. Sustained Outage Causes
In general, sustained outages are the most commonly tracked outage type. In analyses of
sustained outages, utilities tend to exclude scheduled outages, partial power, customer-
related problems, and qualifying major events from their reliability indices calculations.
While this is a valid method for reporting, these outages should be included for internal
review to make utility-level decisions. In this section, we evaluate common causes of
sustained outages for your utility, corresponding region, and for all utilities that use the
eReliability Tracker. It is important to note that in this report, sustained outages are
classified as outages that last longer than five minutes, as defined by IEEE 1366.
Figure 8. Top five causes of sustained outages for all utilities that use the eReliability
Tracker
Figure 9.Top five customer-weighted occurrence rates for common causes of sustained
outages for your utility [1]
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Figure 10. Top five causes of sustained outages in your region
1. For each utility, the number of occurrences for each cause is divided by that utility's customer size (in
1,000s) to create an occurrence rate that can be compared across different utility sizes. ↩
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III.2. Momentary Outage Causes
The ability to track momentary outages can be difficult or unavailable on some systems,
but due to the hazard they pose for electronic equipment, it is important to track and
analyze momentary causes. In this section, we evaluate common causes of momentary
outages for your utility, region, and customer size class as well as common causes for all
utilities that use the eReliability Tracker. Please note that only outages lasting less than
five minutes are classified as momentary, as defined by IEEE 1366. In Figures 11 – 13, for
each utility, the number of occurrences for each cause is divided by that utility's
customer size (in thousands) to create an occurrence rate that can be compared across
different utility sizes.
Figure 11. Top five causes of momentary outages for all utilities that use the eReliability
Tracker
Figure 12.Top five causes of momentary outages for your utility [1]
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Figure 13. Top five causes of momentary outages in your region
1. If your utility has less than eight momentary outages recorded in the eReliability Tracker, this graph will be
blank. ↩
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Thank you for your active participation in the eReliability Tracker service, and we hope
this report is useful to your utility in analyzing your system. If you have any questions
regarding the material provided in this report, please contact:
APPA's Reliability Team
Alex Hofmann
Nathan Mitchell
Ji Yoon Lee
Maddy Wendell
American Public Power Association
2451 Crystal Drive, Suite 1000
Arlington, VA 22202
reliability@publicpower.org
For more information on reliability, visit APPA’s website at PublicPower.org/Reliability.
Copyright 2021 by the American Public Power Association. All rights reserved.
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