2.7 ERMUSR 04-14-2020UTILITIES COMMISSION MEETING
TO: FROM:
ERMU Commission Mike Tietz –Technical Services Superintendent
MEETING DATE: AGENDA ITEM NUMBER:
April 14, 2020 2.7
SUBJECT:
2019 Annual Reliability Report
ACTION REQUESTED:
Receive and file the APPA eReliability Tracker 2019Annual 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 2019, 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
20109207526,14477
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
*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 bythe electric industry to make it
easier to compare performance among utilities, along withERMU’s 2018 and 2019 statistics.
Average Service Availability Index (ASAI)
ASAI is a measure of the average availability of the sub-transmission and distributionsystems
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 2019 ASAI is 99.9951% Availability ERMU’s 2018 ASAI is 99.9980% 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 2019 CAIDI is 60.111 minutes ERMU’s 2018 CAIDI is 58.147 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 minutescustomers would have been out of service if all
customers were out at one time.
ERMU’s 2019 SAIDI is 25.412 minutes ERMU’s 2018 SAIDI was 10.009 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 2019 SAIFI is 0.423 ERMU’s 2018 SAIFI was 0.172
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 2019.
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 2019. Overall, our electric
distribution system is robust, and oursystemreliability is very high.
Please receive the attached American Public Power Association’s (APPA) eReliability Annual
Report 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 our
region or size class.
ATTACHMENT:
APPA eReliability Tracker 2019 Annual Benchmarking Report for ERMU
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Elk River Municipal Utilities
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I. General Overview
Funded by a grant from the Demonstration of Energy & Efficiency Developments (DEED) Program, the
eReliability Tracker Annual Report was created by the American Public Power Association (the
Association) to assist utilities in their efforts to understand and analyze their electric system. This report
focuses on distribution system reliability across the country and is customized to each utility. The data
used to generate this report reflect activity in the eReliability Tracker from January 1, 2019 to December
31, 2019. Note that if you currently do not have a full year of data in the system, this analysis may not
properly reflect your utility's statistics since it only includes data recorded as of February 23, 2020;
therefore, any changes made after that date are not represented herein.
Reliability reflects both historic and ongoing engineering investment decisions within a utility. Proper use
of reliability metrics ensures that a utility is not only performing its intended function, but also is providing
service in a consistent and effective manner. Even though the primary use of reliability statistics is for
self-evaluation, utilities can use these statistics to compare with data from 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 group utilities by size and region to
improve comparative analyses while reducing differences.
Since this report contains overall data for all utilities that use the eReliability Tracker, it is important to
consider the effect that a particularly large or small utility can have on the rest of the data. To ease the
issues associated with comparability, reliability statistics are calculated for each utility with their
respective customer weight taken into account prior to being aggregated with other utilities. This means
that all utilities are equally weighted and all individual statistics are developed on a per customer basis.
The total number of active utilities for 2019 is 502. The aggregate statistics displayed in this report are
calculated from 310 utilities that provided or verified their data and experienced more than two outages
in 2019. Also, utilities that experienced no outages this year, or did not upload any data, will have NULL
or "0" values in their report for their utility-specific data and were not included in the aggregate analysis.
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This report separates utilities into groups of equal numbers of utilities according to their number of
customers served. As seen in Table 1, the customer size distribution of utilities that use the eReliability
Tracker is split into five distinct customer size class groups of approximately 100 utilities per group.
Your utility belongs to customer size class and region .
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Table 1. Customer size range per customer size class
Class 10 -1,207
Class 21,208 - 2,880
Class 32,881 - 6,599
Class 46,600 - 12,465
Class 512,466 - 468,522
Since the utilities considered in this report represent a wide variety of locations across the United States,
each utility is also grouped with all others located in their corresponding American Public Power
Association region. Figure 1 shows the number of utilities using the eReliability Tracker in each
Association region and Figure 2 displays the Association's current United States map of regional divisions.
128
140
120
93
100
80
6262
58
60
43
27
40
15
14
20
Count of Utilities
0
0
12345678910
Association Region
Figure 1. Number of eReliability Tracker utilities per Association region
Figure 2. Association map of regions
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II. IEEE Statistics
When using reliability metrics, a good place to start is with the industry standard metrics found in the IEEE
1366 Guide. For each individual 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).
Due to the differences in how some utilities analyze major events (MEs) relative to their base statistics, it is
important to note how they are calculated and used in this report. An example of a major event includes
severe weather, such as a tornado or hurricane, which can lead to unusually long outages in comparison
to your distribution system's typical outage. In the eReliability Tracker and in this report, the Association's
major event threshold is used, which is a calculation based directly on the SAIDI for specific outage
events, rather than daily SAIDI. The major event threshold allows a utility to remove outages that exceed
the IEEE 2.5 beta threshold for outage events, which takes into account the utility's past outage history up
to 10 years. In the eReliability Tracker, if a utility does not have at least 36 outage events prior to the year
being analyzed, no threshold is calculated; therefore, the field below showing your utility's threshold will
have NULL value 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 (minutes).8.53
The tables in this section can be used by utilities to better understand the performance of their electric
system relative to other utilities nationally and to those within their region or size class. In the SAIDI
section, indices are calculated for all outages with and without major events; furthermore, the data are
broken down to show calculations for scheduled and unscheduled outages. For each of the reliability
indices, 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
system during a specific time period.
Since SAIDI is a sustained interruption index, only outages lasting longer than five minutes are included in
1
the calculations. SAIDI is calculated by dividing the sum of all customer minutes of interruption 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.
Note that in the tables below, scheduled and unscheduled calculations include major events. Also note
that wherever major events are excluded, the exclusion is based on the APPA major event threshold.
Table 2. Average SAIDI for all utilities that use the eReliability Tracker (with and without MEs),
belong to your region, and are grouped in your customer size class
AllNo MEsUnscheduledScheduled
Your utility's SAIDI 25.4125.4125.41NULL
Average eReliability Tracker SAIDI116.7355.63110.0810.74
Average SAIDI for Utilities Within Your Region75.2341.3873.452.64
Average SAIDI for Utilities Within Your Customer Size Class124.0748.59121.343.79
Table 3. Summary statistics of the SAIDI data compiled from the eReliability Tracker
AllNo MEsUnscheduledScheduled
Minimum Value0.000.000.000.00
First Quartile (25th percentile)21.8411.5620.320.18
Median Quartile (50th percentile)56.5726.8154.880.91
Third Quartile (75th percentile)111.8662.19110.544.65
Maximum Value1197.79988.991165.45988.99
300
259.35
250231.51
200
156.06
149.02
150
104.5
92.0292.41
100
75.23
47.48
Average SAIDI (minutes)
50
0
12345678910
Association Regions
Figure 3. Average SAIDI for all utilities that use the eReliability Tracker per region
1Customer 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 time 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 time 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 for all utilities that use the eReliability Tracker, belong to your region, and
are grouped in your customer size class
Your utility's SAIFI0.42
Average eReliability Tracker SAIFI0.90
Average SAIFI for Utilities Within Your Region 0.75
Average SAIFI for Utilities Within Your Customer Size Class0.94
Table 5. Summary statistics of the SAIFI data compiled from the eReliability Tracker
Minimum Value0.00
First Quartile (25th percentile)0.25
Median Quartile (50th percentile)0.57
Third Quartile (75th percentile)1.22
Maximum Value16.45
1.4
1.21
1.19
1.2
1.03
0.97
1
0.87
0.76
0.75
0.72
0.8
0.6
0.48
0.4
0.2
Average SAIFI (Interruptions)
0
12345678910
Association Regions
Figure 4. Average SAIFI for all utilities that use the eReliability Tracker per 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
1
the calculations. It is calculated by dividing the sum of all customer minutes of interruption during that
time period by the number of customers that experienced one or more interruptions during that time
period. This metric reflects the average customer experience (minutes of duration) during an outage.
Table 6. Average CAIDI for all utilities that use the eReliability Tracker, belong to your region, and
are grouped in your customer size class
Your utility's CAIDI 60.11
Average eReliability Tracker CAIDI 169.35
Average CAIDI for Utilities Within Your Region99.62
Average CAIDI for Utilities Within Your Customer Size Class118.34
Table 7. Summary statistics of the CAIDI data compiled from the eReliability Tracker
Minimum Value0.00
First Quartile (25th percentile)67.42
Median Quartile (50th percentile)92.94
Third Quartile (75th percentile)139.83
Maximum Value11512.06
450
414.84
400368.74
350
300
250
184.57
200
124.35
120.98
150119.7
114.85
107.58
99.62
100
Average CAIDI (minutes)
50
0
12345678910
Association Regions
Figure 5. Average CAIDI for all utilities that use the eReliability Tracker per 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
Ћ
momentary interruption.
In this report, an outage with a duration of less than five minutes is classfied as momentary. The index 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 many
smaller utilities may not have the technology to do so; therefore, some utilities may have a MAIFI of zero
Table 8. Average MAIFI for all utilities that use the eReliability Tracker, belong to your region, and
are grouped in your customer size class
Your utility's MAIFI0.0000803
Average eReliability Tracker MAIFI0.65
Average MAIFI for Utilities Within Your Region0.72
Average MAIFI for Utilities Within Your Customer Size Class0.58
Table 9. Summary statistics of the MAIFI data compiled from the eReliability Tracker
Minimum Value0.00
First Quartile (25th percentile)0.00
Median Quartile (50th percentile)0.08
Third Quartile (75th percentile)0.49
Maximum Value26.13
1.71
1.8
1.6
1.4
1.2
1
0.72
0.69
0.8
0.62
0.56
0.6
0.39
0.4
0.25
0.22
0.2
0.02
Average MAIFI (Interruptions)
0
12345678910
Association Regions
Figure 6. Average MAIFI for all utilities that use the eReliability Tracker per region
2Momentary outages can be more difficult to track and many smaller utilities may not have the technology to do so; therefore, some
utilities may have a MAIFI of zero.
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II.5. Average Service Availability Index (ASAI)
ASAI is defined as 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
time period analyzed. It is caclulated by dividing the total hours 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 time period.
Table 10. Average ASAI for all utilities that use the eReliability Tracker, belong to your region, and
are grouped in your customer size class
Your utility's ASAI (%)99.9951
Average eReliability Tracker ASAI99.9778
Average ASAI for Utilities Within Your Region99.9856
Average ASAI for Utilities Within Your Customer Size Class99.9766
Table 11. Summary statistics of the ASAI data compiled from the eReliability Tracker
Minimum Value99.7721
First Quartile (25th percentile)99.9787
Median Quartile (50th percentile)99.9892
Third Quartile (75th percentile)99.9958
Maximum Value100.0000
99.99199.982499.985699.9899.970299.955999.971899.982699.9518
100.00
80.00
60.00
40.00
Average ASAI (%)
20.00
0.00
12345678910
Association Regions
Figure 7. Average ASAI for all utilities that use the eReliability Tracker per region
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II.6. 2018 Energy Information Administration (EIA) Form 861 Data
Form EIA-861 collects information on the status of electric power industry participants involved in the
generation, transmission, distribution, and sale of electric energy in the United States, its territories, and
Puerto Rico.
EIA surveys electric power utilities annually through EIA Form 861 to collect electric industry data and
subsequently make that data available to the public. In 2014, EIA began publishing reliability statistics in
their survey from utility participants; therefore, the Association included EIA reliability statistics in this
report for informational purposes. Please note that the following data includes 174 investor-owned, 553
3
rural cooperative, and 389 public power utilities that were large enough to be required to fill out the full
EIA 861, not the EIA 861-S form (for smaller entities). In addition, since the collection and release of
EIA form data lags by a year, the data provided here is based on the 2018 data that was published in
October 1, 2019. Therefore, it is suggested that the aggregate statistics contained herein be used only
as an informational tool for further comparison of reliability statistics.
In Table 12 and Table 13, an entity calculates SAIDI, SAIFI, and determines major event days in
accordance with the IEEE 1366-2003 or IEEE 1366-2012 standard.
http://publicpower.org/reliability. Although EIA collected other reliability-related data, the tables below
only include SAIDI and SAIFI data. The full set of data can be downloaded at:
http://www.eia.gov/electricity/data/eia861/
Table 12. Summary statistics of the SAIDI data collected in 2018 and published in 2019 by EIA
IEEE Method
AllNo MEDs
Average327.85142.76
Minimum Value1.130.00
First Quartile (25th percentile)80.8252.94
Median Quartile (50th percentile)154.91100.36
Third Quartile (75th percentile)320.10161.20
Maximum Value8092.006356.07
Table 13. Summary statistics of the SAIFI data collected in 2018 and published in 2019 by EIA
IEEE Method
AllNo MEDs
Average1.641.27
Minimum Value0.030.00
First Quartile (25th percentile)0.830.65
Median Quartile (50th percentile)1.331.06
Third Quartile (75th percentile)2.031.56
Maximum Value13.0311.31
3389 public power utilities include entities classified by EIA as municipal, political subdivision, and state.
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II.7. Analysis of Miles of Line and Interruptions
Benchmarking metrics were created to 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, the customer density distribution of utilities that
use the eReliability Tracker is split into five distinct customer density size groups of approximately 64
4
utilities. By using the miles of line-related metrics shown in Table 14 and Table 15, utilities can
benchmark 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.
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Your utility's total miles of line:
95
Your utility's overhead miles of line:
220
Your utility's underground miles of line:
Table 14. Analysis of total miles of line and interruptions
Interruptions per MileCustomers Interrupted Minutes of Interruption
per Mileper Mile
Your Utility0.1916.5219.22
Average for eReliability Tracker Utilities0.4338.50137.37
Average for Utilities Within Your Region0.5038.1490.81
39.62
Your utility's average customer density (customers per mile):
Your utility belongs to customer density class
2
Table 15. Total miles of line analysis by customer density class
Customer Density Class Customer Density Interruptions per MileCustomers Minutes of
(Customers per Mile)RangeInterrupted per MileInterruption per Mile
Class 11 -300.2318.49108.43
Class 231 - 450.3522.7956.89
Class 346 - 620.4828.05304.29
Class 463 - 880.5040.75132.25
Class 589 - 16600.5982.4793.46
4Customer density classes include eReliability Tracker utilities that either provided their miles of line data to Platts or recorded their data in the
eReliability Tracker.
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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 a different set of causes more prevalent to a specific group of utilities. The following
section of this report include graphs depicting common causes of outages for your individual utility, all
utilities in your region, and all utilities using the eReliability Tracker. The 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; in
order to avoid skewing the data towards 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. For instance, a customer-weighted occurrence rate of "1"
means 1 outage of that outage cause per 1,000 customers on average in 2019.
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.
III.1. Sustained Outage Causes
In general, sustained outages are the most commonly tracked outage type. In many 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.
1.41.27
1.2
1
0.71
0.8
0.6
0.38
0.37
0.29
0.4
Occurrence Rates
0.2
0
TreeStormEquipmentSquirrelUnscheduled
TreesHumanWeatherSquirrelUnknown
Outage Causes Types
Figure 8. Top five customer-weighted occurrence rates for common causes of sustained outages
Ў
for all utilities that use the eReliability Tracker Service
5For each utility, the number of occurrences for each cause is divided by that utility's customer size (in 1,000s) to create an occurence rate
that can be compared across different utility sizes.
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1.81.68
1.53
1.6
1.4
1.2
0.96
1
0.72
0.8
0.57
0.6
0.4
Occurrence Rates
0.2
0
SquirrelTreeElectrical FailureLightningEquipment Worn
S-firstS-seconds-thirdS-fourthS-fifth
Out
Outage Cause Types
Ў
Figure 9. Top five customer-weighted causes of sustained outages for your utility
1.87
2
1.5
0.87
1
0.53
0.47
0.5
0.15
Occurrence Rates
0
Electrical FailureUtility Maintenance
UnscheduledSquirrelTree
S-firstS-secondS-thirdS-fourthS-fifth
and Repairs
Outage Cause Types
Ў
Figure 10. Top five customer-weighted occurrence rates for sustained outage causes in your region
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II.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.
0.160.15
0.14
0.12
0.12
0.1
0.08
0.050.05
0.06
0.04
Occurrence Rates
0.02
0.002
0
UnknownUtility Maintenance Equipment EquipmentStorm
TreesHumanWeatherSquirrelUnknown
and RepairsReplacement
Outage Cause Types
Figure 11. Top five customer-weighted occurrence rates for common causes of momentary
Ў
outages for all utilities that use the eReliability Tracker Service
0.2
0.19
0.15
0.1
0.05
Occurrence Rates
0000
0
NoneNoneNone
SquirrelTreesNoneHumanWeatherSquirrelUnknown
Outage Cause Types
ЎͲ Џ
Figure 12. Top five customer-weighted causes of momentary outages for your utility
6 If your utility has less than eight momentary outages recorded in the eReliability Tracker, this graph will be blank.
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0.3
0.24
0.25
0.2
0.15
0.1
0.05
0.04
Occurrence Rates
0.03
0.028
0.05
0
TreeSquirrelUnknownUnscheduledUtility Maintenance
M-firstM-secondM-thirdM-fourthM-fifth
and Repairs
Outage Cause Types
Figure 13. Top five customer-weighted occurrence rates for momentary outage causes in your
Ў
region
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
Ji Yoon Lee
American Public Power Association
2451 Crystal Drive, Suite 1000
Arlington, VA 22202
reliability@publicpower.org
Copyright 2020 by the American Public Power Association. All rights reserved.
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