5.4. ERMUSR 03-12-2019 Elk River
Municipal Utilities UTILITIES COMMISSION MEETING
TO: FROM:
ERMU Commission Mike Tietz—Technical Services Superintendent
MEETING DATE: AGENDA ITEM NUMBER:
March 12, 2019 5.4
SUBJECT:
2018 Annual Reliability Report
ACTION REQUESTED:
Receive and file the APPA eReliability Tracker 2018 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 a number of parts of this chapter as a Distribution Reliability Standard policy requiring
annual reporting on system reliability.
DISCUSSION:
In 2018, our reliability index numbers remain excellent. 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
2009 9170 46,706 49
2010 9207 526,144 77
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
A number of reliability indexes are used in the electric industry to make it easier to compare
performance of electric utilities. Listed below are the reliability indexes along with ERMU's
2017 and 2018 statistics. Also attached is the American Public Power Association's (APPA)
Page 1 of 3
78
eReliability Annual Report. It contains published averages that 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.
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 2018 ASAI is 99.9980%Availability ERMU's 2017 ASAI is 99.9938%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 sustained' interruption in the time period and dividing this by the number of
customers experiencing one or more sustained' 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 2018 CAIDI is 58.147 minutes ERMU's 2017 CAIDI is 103.718 minutes
System Average Interruption Duration Index(SAID!)
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
sustained' 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 2018 SAIDI is 10.009 minutes ERMU's 2017 SAID! was 32.3938 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 sustained' interrupted
customers in a time period by the average number of customers served. The resulting unit is
"interruptions per customer."
ERMU's 2018 SAIFI is 0.172 ERMU's 2017 SAIFI was 0.3123
' Only outages lasting longer than five minutes are included in the calculations, as defined by IEEE 1366.
Page 2 of 3
79
Elk River
Municipal Utilities UTILITIES COMMISSION MEETING
TO: FROM:
ERMU Commission Mike Tietz—Technical Services Superintendent
MEETING DATE: AGENDA ITEM NUMBER:
March 12, 2019 5.4
SUBJECT:
2018 Annual Reliability Report
ACTION REQUESTED:
Receive and file the APPA eReliability Tracker 2018 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 a number of parts of this chapter as a Distribution Reliability Standard policy requiring
annual reporting on system reliability.
DISCUSSION:
In 2018, our reliability index numbers remain excellent. 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
2009 9170 46,706 49
2010 9207 526,144 77
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
A number of reliability indexes are used in the electric industry to make it easier to compare
performance of electric utilities. Listed below are the reliability indexes along with ERMU's
2017 and 2018 statistics.Also attached is the American Public Power Association's (APPA)
Page 1 of 3
78
eReliability Annual Report. It contains published averages that 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.
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 2018 ASAI is 99.9980%Availability ERMU's 2017 ASAI is 99.9938%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 sustained' interruption in the time period and dividing this by the number of
customers experiencing one or more sustained' 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 2018 CAIDI is 58.147 minutes ERMU's 2017 CAIDI is 103.718 minutes
System Average Interruption Duration Index(SAID!)
SAID! 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
sustained' 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 2018 SAIDI is 10.009 minutes ERMU's 2017 SAID! was 32.3938 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 sustained' interrupted
customers in a time period by the average number of customers served. The resulting unit is
"interruptions per customer."
ERMU's 2018 SAIFI is 0.172 ERMU's 2017 SAIFI was 0.3123
' Only outages lasting longer than five minutes are included in the calculations, as defined by IEEE 1366.
Page 2 of 3
79
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 2018.
Outage Cause Count View
Squirrel 17
Equipment Worn Out 6 ta!
18% Vehicle Acciden 5
Tree 5
squirrel Electrical Failure 4
33%
Unknown Contractor-Dig-In 3
4%
Unknown 2
Contractor-Dig-I Unknown/Other
Contact with Foreign Object 2 4J
VJiitllife 1
Electrical Failure
8% Lightning 1 C�
[Equipment 1 c�
[Heat 1 ,i- _
Wam out
Tree 1
10%
[Eire 1 fl
Vehicle Accident
10% Total 51
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 customer actually experienced in 2018. Overall, our electric
distribution system is robust and our reliability is very high.
ATTACHMENT:
• APPA eReliability Tracker 2018 Annual Benchmarking Report for ERMU
Page 3 of 3
80
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Elk River Municipal Utilities
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, 2018 to December
31, 2018. 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 18, 2019;
therefore, any changes made after that date are not represented herein.
I. General Overview
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 2018 are 460. The aggregate statistics displayed in this report are
calculated from 277 utilities that provided or verified their data and experienced more than two outages in
2018. Also, utilities that experienced no outages this year, or did not upload any data, will have None/Null
values in their report for their utility-specific data and were not included in the aggregate analysis.
2
82
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 92 utilities per group.
Your utility belongs to customer size class 4 and region 3.
Table 1
Customer size range per customer size class
Class 1 0-1,337
Class 2 1,338 -3,003
Class 3 3,004-6,679
Class 4 6,680- 12,262
Class 5 12,263-650,000
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.
Figure 1
Number of eReliability Tracker utilities per Association region
140 - 129
• 120 -
• 100 - 94
80 - 66 60
c 60 - 41
27
o 20 - 16 13 13
0
• 0 ■ MI
1 2 3 4 5 6 7 8 9 10
Association Region
Figure 2
Association map of regions
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83
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).
When collecting the necessary data for reliability indices, utilities often take differing approaches. Some
utilities prefer to include information as detailed as circuit type or phases impacted, while others include
only the minimum required. In all cases, the more details a utility provides, the more practical their
analysis will be. As a basis for calculating these statistics in the eReliability Tracker, the following are
required:
- Total number of customers served on the day of the outage
- Start and end date/time of the outage
- Number of customers that lost power
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 could be
severe weather, such as a tornado or thunderstorm, 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 outage events, rather
than event days. The major event threshold allows a utility to remove outages that exceed the IEEE 2.5
beta threshold for 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 be blank 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 11.9147 (minutes).
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.
1 If there is no major event threshold calculated for your utility,these fields are left blank and the calculations in this report including Major Events and excluding
them will be the same.Your utility must have at least 36 outage events recorded in the eReliability Tracker in order to calculate a Major Event Threshold.
4
84
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
the calculations. SAIDI is calculated by dividing the sum of all customer interruption durations within the
specified time frame by the average number of customers served during that period. For example, a utility
with 100 customer minutes of outages 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
All No MEs Unscheduled Scheduled
Your utility's SAIDI 10.009 10.009 9.949 0.057
Average eReliability Tracker SAIDI 202.449 69.0185 185.0572 17.463
Average SAIDI for Utilities Within Your Region 133.1295 67.3469 131.5411 1.5907
Average SAIDI for Utilities Within Your Customer Size Class 221.2008 34.0534 206.258 14.9341
Table 3
Summary statistics of the SAIDI data compiled from the eReliability Tracker
All No MEs Unscheduled Scheduled
Minimum Value 0.283 0.283 0.186 0
First Quartile(25th percentile) 21.647 12.203 19.69 0
Median Quartile(50th percentile) 53.2225 27.084 52.313 0.134
Third Quartile(75th percentile) 141.0617 63.238 131.51 2.086
Maximum Value 8746.1 1843.61 8743.182 1580.062
Figure 3
Average SAIDI for all utilities that use the eReliability Tracker per region
900-
800 767.7695
w 700-
E
600-
0 500-
.4 400-
315.8426 275.3225
m 300- 234.8737
200- 174.2614 141.5934
126.5944 133.1295 103.0168
100 ■ 111
■ . .
1 2 3 4 5 6 7 8 9 10
Association Regions
5
85
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 SAIFI 0.172
Average eReliability Tracker SAIFI 0.9541
Average SAIFI for Utilities Within Your Region 0.6658
Average SAIFI for Utilities Within Your Customer Size Class 0.7373
Table 5
Summary statistics of the SAIFI data compiled from the eReliability Tracker
Minimum Value 0.0071
First Quartile(25th percentile) 0.284
Median Quartile (50th percentile) 0.667
Third Quartile (75th percentile) 1.223
Maximum Value 7.535
Figure 4
Average SAIFI for all utilities that use the eReliability Tracker per region
1.6 -
c 1.4 - 1.3146 1.3898
o 1.1986
1.2 1.0079 1.0152
1 - 0.881
• 0.8 - 0.6658 0.6529 0.7024
a 0.6 -
to
a> 0.4 -
rn
1- 0.2 -
1 2 3 4 5 6 7 8 9 10
Association Regions
6
86
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. It is calculated by dividing the sum of all customer interruption durations 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 58.147
Average eReliability Tracker CAIDI 180.7475
Average CAIDI for Utilities Within Your Region 173.9667
Average CAIDI for Utilities Within Your Customer Size Class 276.669
Table 7
Summary statistics of the CAIDI data compiled from the eReliability Tracker
Minimum Value 10.413
First Quartile (25th percentile) 60.692
Median Quartile(50th percentile) 86.822
Third Quartile(75th percentile) 137.545
Maximum Value 7981.064
Figure 5
Average CAIDI for all utilities that use the eReliability Tracker per region
800 - 733.1139
w 700 -
a)
600 -
c
E 500 -
Q 400 -
m 300 -
13)
200 - 122.2303 149.4425
179.4855 173.9667 177.7918
138.1305 181.1176
■ I 104.9817
100 -
1 2 3 4 5 6 7 8 9 10
Association Regions
7
87
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 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. 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 MAIFI 0.0002
Average eReliability Tracker MAIFI 0.2938
Average MAIFI for Utilities Within Your Region 0.3142
Average MAIFI for Utilities Within Your Customer Size Class 0.2548
Table 9
Summary statistics of the MAIFI data compiled from the eReliability Tracker
Minimum Value 0
First Quartile(25th percentile) 0
Median Quartile(50th percentile) 0
Third Quartile(75th percentile) 0.143
Maximum Value 7.687
Figure 6
Average MAIFI for all utilities that use the eReliability Tracker per region
N 0.8 - 0.7016
0.7 -
.2
a
• 0.6 -
L
0.5 -
0.3746
LL 0.4 - 0.3142 0.3169
< 0.3 - 0.2366 0.2214
0.1888
a 0.2 - 0.1108 II
co
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0.0447
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1 2 3 4 5 6 7 8 9 10
Association Regions
8
88
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 (%) 99.998
Average eReliability Tracker ASAI 99.9615
Average ASAI for Utilities Within Your Region 99.9747
Average ASAI for Utilities Within Your Customer Size Class 99.9579
Table 11
Summary statistics of the ASAI data compiled from the eReliability Tracker
Minimum Value 98.3359
First Quartile(25th percentile) 99.9731
Median Quartile(50th percentile) 99.9899
Third Quartile (75th percentile) 99.9961
Maximum Value 99.9999
Figure 7
Average ASAI for all utilities that use the eReliability Tracker per region
99.9554 99.9758 99.9747 99.8538 99.9399 99.9475 99.9803 99.9668 99.9742
00.00!i1IIIIII ! II
20.00 -
0.00
1 2 3 4 5 6 7 8 9 10
Association Regions
9
89
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 investor-owned, rural
cooperative, and 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 more than a year, the data provided here is based on 2017 data only. Therefore, it is suggested that
the aggregate statistics contained herein be used only as an informational tool for further comparison of
reliability statistics.
In the table, if an entity calculates SAIDI, SAIFI, and determines major event days in accordance with the
IEEE 1366-2003 or IEEE 1366-2012 standard, they are included under the "IEEE Method" columns. If the
entity calculates these values via another method, they are included under the "Other Method" columns.
For more general information on reliability metrics you can see the Association's website at
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 this link:
http://www.eia.gov/electricity/data/eia861/
Table 12
Summary statistics of the SAIDI data collected in 2017 and published in 2018 by EIA
IEEE Method Other Method
All No MEDs All No MEDs
Average 377.6190 134.5683 383.0213 132.7504
Minimum Value 0.2750 0.0000 0.3000 0.0000
First Quartile(25th percentile) 83.2050 55.4410 41.5000 27.5873
Median Quartile(50th percentile) 169.6020 94.9580 102.2580 78.0145
Third Quartile (75th percentile) 321.0500 161.9000 247.5543 150.7025
Maximum Value 16472.0710 2796.1870 17182.0000 2796.1870
Table 13
Summary statistics of the SAIFI data collected in 2017 and published in 2018 by EIA
IEEE Method Other Method
All No MEDs All No MEDs
Average 1.7178 1.3091 1.4603 1.0628 Minimum Value 0.0030 0.0000 0.0040 0.0000
First Quartile(25th percentile) 0.9000 0.6900 0.5770 0.3940
Median Quartile(50th percentile) 1.3700 1.0870 1.0090 0.8370
Third Quartile(75th percentile) 2.0010 1.5200 1 1.8930 1.4545
Maximum Value 83.2050 55.4410 12.8000 9.0480
10
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Analysis of Miles of Line and Interruptions
Benchmarking metrics were created to help utilities explore the relationship between outages,
overhead/underground line exposure, and customer density. More specifically, by using interruptions per
overhead/underground mile of line and customers per mile 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.
Your utility's overhead miles of line as reported by Platts: 95
Table 14
Analysis of overhead miles of line and interruptions
Interruptions per Mile ! Customers per Mile Minutes per Mile
Your Utility 0.5578 128.4526 49.4315
Average for eReliability Tracker Utilities 0.984 100.745 186
Average for Utilities Within Your Region 0.9296 118.6913 160.8007
Your utility's underground miles of line as reported by Platts: 220
Table 15
Analysis of underground miles of line and interruptions
Interruptions per Mile Customers per Mile Minutes per Mile
Your Utility 0.2409 55.4681 21.3454
Average for eReliability Tracker Utilities 8.6341 613.4802 1340
Average for Utilities Within Your Region 2.4516 262.7144 590.3475
11
91
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
sections 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 the figures below, the data represent the number of
occurrences for each group of 1000 customers. For instance, a customer-weighted occurrence rate of"1"
means 1 outage of that outage cause per 1000 customers on average in 2018.
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.
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.
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Figure 8
Top five customer-weighted occurrence rates for common causes of sustained outages for all
utilities that use the eReliability Tracker Service 2
1.4 - 1.2194
1.2 -
N
To
a, 0.8 -
m 0.6 - 0.4641
• 0.4 - 0.3473 0.3259 0.2944
O 0.2 -
0
Tree Equipment Electrical Failure Squirrel Utility Maintenance
and Repairs
Outage Causes Types
Figure 9
Top five customer-weighted causes of sustained outages for your utility
1.6 - 1.475
w 1.4 -
m 1.2 -
IX 1 -
a)
c 0.8 -
• 0.6 - 0.4916 0.4097 0.4097 0.3277
c.)• 0.4 -
O 0.2 -
0
Squirrel Equipment Worn Out Vehicle Accident Tree Electrical Failure
Outage Cause Types
Figure 10
Top five customer-weighted occurrence rates for sustained outage causes in your region 2
1 — 0.8716
m 0.8 -
`° 0.5689
a)• 0.6 - 0.451 0.4287
• 0.4 -
� 0.2 -
0.1564
0
0
Squirrel Utility Maintenance Electrical Failure Wildlife Unknown
and Repairs
Outage Cause Types
2
For each utility,the number of occurrences for each cause is divided by that utility's customer size(in 1000s)to create an occurence rate that can be compared
across different utility sizes.
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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.
Figure 11
Top five customer-weighted occurrence rates for common causes of momentary outages for all
utilities that use the eReliability Tracker Service 2
0.14 - 0.1321
0.12 -
en
°'• 0.1 - 0.0904
0.0812
0.08 - 0.0633 0.0598
0.06 -
• 0.04 -
O 0.02 -
0 1 1 I 1
Utility Maintenance and Unknown Equipment Replacement Failure of Greater Equipment
Repairs Transmission
Outage Cause Types
Figure 12
Top five customer-weighted causes of momentary outages for your utility2'3
0.1
0.0819 0.0819
a, 0.08
a)
▪ 0.06
co
;v 0.04
O 0.02
O 0 0 0
0
Electrical Failure Vehicle Accident None None None
Outage Cause Types
3
If your utility has less than eight momentary outages recorded in the eReliability Tracker,this graph will be blank.
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94
Figure 13
Top five customer-weighted occurrence rates for momentary outage causes in your region2
0.2 - 0.1848
N
°.3 0.15 -
ca
re 0.1114
m
c 0.1 -
0.0528
00.05 0.0304
0 0.0182
0 _11111______,
Unknown Ice Utility Maintenance Storm Utility Human Error
and Repairs
Outage Cause Types
Thank you for using the eReliability Tracker,
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
Michael J. Hyland
Alex Hofmann
Tyler Doyle
Ji Yoon Lee
American Public Power Association
2451 Crystal Drive, Suite 1000
Arlington, VA 22202
reliability@publicpower.org
Copyright 2019 by the American Public Power Association. All rights reserved.
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95
AMERICAN
PUBLIC
n
P ..RTM
ASSOCIATION
Powering Strong Communities
2451 Crystal Drive
Suite 1000
Arlington.VA 22202-4804
www.PublicPower.org
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