5.3 ERMUSR 03-13-2018 Elk River
Municipal Utilities UTILITIES COMMISSION MEETING
TO: FROM:
ERMU Commission Mike Tietz—Technical Services Superintendent
MEETING DATE: AGENDA ITEM NUMBER:
March 13, 2018 5.3
SUBJECT:
2017 Annual Reliability Report
ACTION REQUESTED:
Receive and file the APPA eReliability Tracker 2017 Annual Benchmarking Report or 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 2017, our reliability index numbers remain excellent. These reliability index numbers reflect
the condition of our well-built electrical system as well as the fantastic response time from our
local line crews. This also reflects the local accountability, long term visioning on system
design, and ongoing system maintenance.
With all that being said, why do we measure reliability?
The answer is really quite simple; Reliability indexes help us improve service to our customers
by showing us trends over time that help us make informed decisions in how we build and
maintain the system.
Another benefit provided by these indexes is by benchmarking our performance with other
electric utilities. A number of reliability indexes are used in the electric industry to make these
comparisons easier. However, not all utilities gather the data exactly the same. The following are
the most common ones used in the industry and are the ones we are measured on. A brief
explanation of the index is provided to help understand what is being measured.
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.
Page 1 of 3
201
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."
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.
Momentary Average Interruption Frequency Index(MAIFI)
MAIFI is defined as the average number of times that a customer on the system will experience a
momentary interruption. It is determined by dividing the total number of momentary customer
interruptions by the average number of customers served. The resulting unit is"interruptions per
customer."
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.
Listed below in Table 1 is a summary for the 2017 reliability indexes. This table includes 2016
reliability indexes for comparison. Attached is the American Public Power Association's (APPA)
eReliability Annual Report which 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.
2017 Electric Reliability Summary
ERMU APPA Region 3 APPA Customer Class 4
Index
2017 2016 2017 2016 2017 2016
SAIDI 32.3938 41.0234 100.7792 88.3391 230.6849 85.4668
SAIFI 0.3123 0.2727 0.7275 0.6310 0.8991 0.7013
CAIDI 103.7180 150.4193 111.4538 153.2071 227.8248 116.6985
MAIFI 0.0012 0.0001 0.6860 0.5327 0.3090 0.4400
ASAI 99.9938 99.9922 99.9808 99.9839 99.9561 99.9838
Table 1
' Only outages lasting longer than five minutes are included in the calculations, as defined by IEEE 1366.
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 2017.
Page 2 of 3
202
2017 ERMU Outage Causes
Outage Cause Count View
Tree111111
Squirrel
+�; ......... .w.was
Tree Vehicle Accident 5
20%
Electrical Failure
Other lightning 2 a
33%
Equipment Worn Out 2 4�
Equipment Damage 2
Unknown/Other 2
Storm 2 4
r Squirrel
13% Contact with Foreign Object 2
�
Weather 1 4
[Unknown 1
c Wildlife 1
Equipment Damage
5% 'Equipment s 1 4
Vehicle Accident 1Contractor-D
Equipment Worn Out 13% t
5% [Load Swa
Lightning
5% Electrical Failure f Wind
8%
Total 40
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 actually experienced in 2017. Overall, our electric
distribution system is robust and our reliability is very high.
ATTACHMENT:
• APPA eReliability Tracker 2017 Annual Benchmarking Report for ERMU
Page 3 of 3
203
• 1iio •
A. w♦an
too
11111 NI se
O
+.
t AI III♦
ANNUAL
�■■�
c,41 eRELIABILITY TRACKER
AMERICAN
PUBLIC
FW:ERTM
ASSOCIATION
Powering Strong Communities
204
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, 2017 to December
31, 2017. 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 3, 2018;
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 aggregate statistics displayed in this report are calculated from utilities that experienced more than
two outages in 2017. 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.
The aggregate statistics provided in the following sections of the report are based on data from 253
utilities.
2
205
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 85 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: 0-1,497
Class 2: 1,498-3,126
Class 3: 3,127-6,797
Class 4: 6,798 - 12,695
Class 5: 12,696-650,000
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
70 - 60
57
a 60 -
50 - 45
40 -
° 30 - 23 25
0 17 9 10
20
10 ,
II
3 4 5 6 7 8 9 10
Association Region
Figure 2
Association map of regions
REGION!
R[61OM 3 MOONS
hili", Rl6N)Ilt Rrt61oN1 lr
11161ON f
Jag. ""ilk
REGION to
3
206
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 8.6726 (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
207
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: 32.3938 17.4218 30.6682 1.7254
Average eReliability Tracker SAIDI 161.7605 62.1498 157.4675 4.4295
Average SAIDI for Utilities Within Your Region 100.7792 52.9737 99.1595 1 1.72
Average SAIDI for Utilities Within Your Customer Size Class 230.6849 70.9849 226.9916 3.7064
Table 3
Summary statistics of the SAIDI data compiled from the eReliability Tracker
All No MEs Unscheduled Scheduled
Minimum Value 0.1282 0.1282 0.1282 0
First Quartile (25th percentile) 23.6535 10.6552 20.5479 0
Median Quartile(50th percentile) 54.863 27.2189 52.3865 0.097
Third Quartile(75th percentile) 120.8739 60.6194 114.7618 1.3001
Maximum Value 5208.0378 1412.0408 5199.7198 208
Figure 3
Average SAIDI for all utilities that use the eReliability Tracker per region
500 -448.1083 461.5984
r 450 -
4 400 -
350 -
0 300 -7t 250 - 227.6868
' 200 - 179.1688
`° 150 125.3523
100.7792 95.5004 82.8786
100 - I 56.0832 . .
50 -
1 2 3 4 5 6 7 8 9 10
Association Regions
5
208
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: 0.3123
Average eReliability Tracker SAIFI 0.8515
Average SAIFI for Utilities Within Your Region 0.7275
Average SAIFI for Utilities Within Your Customer Size Class 0.8991
Table 5
Summary statistics of the SAIFI data compiled from the eReliability Tracker
Minimum Value 0.0009
First Quartile(25th percentile) 0.2812
Median Quartile(50th percentile) 0.6357
Third Quartile(75th percentile) 1.0948
Maximum Value 8.0499
Figure 4
Average SAIFI for all utilities that use the eReliability Tracker per region
1 8 - 1.7043
0 1.6 -
. 1.4 - 1.3118
1.2 - 1.1042
• 1 - 0.8483 0.9241
E (1.8 - 0.7409 0.7275 0.6949 0.6488
Q
a)
Cip 0.6 -
0.4 -
Q 0.2 - 0
1 2 3 4 5 6 7 8 9 10
Association Regions
6
209
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: 103.718
Average eReliability Tracker CAIDI 321.6103
Average CAIDI for Utilities Within Your Region 111.4538
Average CAIDI for Utilities Within Your Customer Size Class 227.8248
Table 7
Summary statistics of the CAIDI data compiled from the eReliability Tracker
Minimum Value 11.7835
First Quartile(25th percentile) 60.0011
Median Quartile(50th percentile) 94.8976
Third Quartile(75th percentile) 151.0141
Maximum Value 22979.18
Figure 5
Average CAIDI for all utilities that use the eReliability Tracker per region
700 - 634.764
600 - 525.2002
c 500 -
E
0 400 - 340.985
300 -
200 - 151.7638 134.1772 171.8783
111.4538
89.589 95.6323
100 - ■ ■ , ■ .
0
1 2 3 4 5 6 7 8 9 10
Association Regions
7
210
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: 0.0012
Average eReliability Tracker MAIFI 0.3515
Average MAIFI for Utilities Within Your Region 0.686
Average MAIFI for Utilities Within Your Customer Size Class 0.309
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) 0.1166
Maximum Value 25.0421
Figure 6
Average MAIFI for all utilities that use the eReliability Tracker per region
0.8 -
0.686 0.6716
O• 0.7 -
0
• 0.6 -
i 0.5 -
E 0.4 - 0.3432
0.2673 0.2899
0.3 - 0.2283
m 0.1806
crip 0.2 0.0935
0.1 - 0.0197 . 0
0
1 2 3 4 5 6 7 8 9 10
Association Regions
8
211
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 (%): 99.9938
Average eReliability Tracker ASAI 99.9693
Average ASAI for Utilities Within Your Region 99.9808
Average ASAI for Utilities Within Your Customer Size Class 99.9561
Table 11
Summary statistics of the ASAI data compiled from the eReliability Tracker
Minimum Value 99.0091
First Quartile(25th percentile) 99.9779
Median Quartile(50th percentile) 99.9896
Third Quartile(75th percentile) 99.9954
Maximum Value 99.9999
Figure 7
Average ASAI for all utilities that use the eReliability Tracker per region
99.9147 99.9761 99.9808 99.9894 99.9566 99.9121 99.9818 99.9849 99.9677
100.00
¢ 80.00 -
u)
m 60.00 -
rn
a) 40.00 -
20.00 -
0
0.00
1 2 3 4 5 6 7 8 9 10
Association Regions
9
212
2016 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 2016 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.
Additionally, it looks as though a number of utilities submitted incorrect data, which shows itself most in
the average SAIFI numbers. 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 compiled from 2016 data collected by EIA
IEEE Method Other Method
All No MEDs All No MEDs
Average 314.2593 128.6160 210.6055 111.4045
Minimum Value 0.2840 0.0000 0.1740 0.1740
First Quartile (25th percentile) 81.7025 54.3800 31.4225 23.5100
Median Quartile (50th percentile) 154.8600 101.9000 97.0000 80.9000
Third Quartile(75th percentile) 292.7500 164.5150 205.1620 153.3400
Maximum Value 6957.4700 1099.0700 3163.4000 648.0000
Table 13
Summary statistics of the SAIFI data compiled from 2016 data collected by EIA
IEEE Method Other Method
All No MEDs All No MEDs
Average 1.6569 1.2989 1.3222 1.0575
Minimum Value 0.0040 0.0000 0.0000 0.0000
First Quartile (25th percentile) 0.8800 0.6700 0.4740 0.3900
Median Quartile (50th percentile) 1.3400 1.0700 1.0540 0.9300
Third Quartile(75th percentile) 2.0600 1.5600 1.7920 1.4400
Maximum Value 29.0000 28.0200 13.0000 5.8800
10
213
Analysis of Miles of Line and Interruptions
Benchmarking metrics were created to help utilities explore the relationship between outages, overhead
line exposure, and customer density. More specifically, by using interruptions per overhead 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 Ventyx: 95
Table 14
Analysis of overhead miles of line and interruptions
Interruptions per Mile Customers per Mile
Your Utility: 0.3895 120.9368
Average for eReliability Tracker Utilities 0.9053 104.7849
Average for Utilities Within Your Region 0.8384 122.3345
11
214
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 2017.
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.
12
215
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 - 1.2187
1.2 - 1.0485
1.0099
rco 1 - 0.8259
a 0.8 -
c 0.579
m 0.6 -
o 0.4 -
U
0.2 -
0
Tree Unknown Squirrel Equipment Electrical Failure
Outage Causes Types
Figure 9
Top five customer-weighted causes of sustained outages for your utility
0.8 - 0.6963
0.7 -
0.6 -
W 0.5 - 0.4351
a)
a)0.4 - 0.2611 0.2611
0.3 - 0.174
8 0.2 -
0.1 -
0
Tree Squirrel Vehicle Accident Electrical Failure Lightning
Outage Cause Types
Figure 10
Top five customer-weighted occurrence rates for sustained outage causes in your region 2
1.4 1.2111 1.2041
• 1.2 1.1204
a)
co 1 0.8252 0.8229
0 0.8
ami 0.6
� 0• .4
U
0• .2
0
Squirrel Weather Tree Wildlife Utility Maintenance
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.
13
216
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
0.25 -
co 02 - 0.1914
is
0.15 -
U
0.1 -
0.0578
0 0.0522
p 0.05 - 0.0383 0.038
0
Unknown Utility Maintenance and Customer Service Equipment Replacement Equipment
Repairs
Outage Cause Types
Figure 12
Top five customer-weighted causes of momentary outages for your utility2,3
0.2 - 0.174
m 0.15 -
m 0.1 - 0.087
U
8 0.05 -
0 0 0
0
Unknown/Other Unknown 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.
14
217
Figure 13
Top five customer-weighted occurrence rates for momentary outage causes in your region
0.2 0.1883
m 0.15 0.1278 0.1255
0.1
°2 0.0697 0.0628
8 0.05
O
0
Utility Human Error Utility Maintenance Unknown Unknown/Other Weather
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
Tanzina Islam
Christina Ospina
Ethan Epstein
American Public Power Association
2451 Crystal Drive, Suite 1000
Arlington, VA 22202
reliability@publicpower.org
Copyright 2018 by the American Public Power Association. All rights reserved.
15
218
AMERICAN
PUBLIC
POWER,.
ASSOCIATION
Powering Strong Communities
2451 Crystal Drive
Suite 1000
Arlington.VA 22202-4804
www.PublicPower.org
219