4.1. ERMUSR 03-17-2015 i
Elk River
Municipal Utilities UTILITIES COMMISSION MEETING
TO: FROM:
Elk River Municipal Utilities Commission Wade Lovelette—Technical Services
John Dietz—Chair Superintendent
Al Nadeau—Vice Chair
Daryl Thompson—Trustee
MEETING DATE: AGENDA ITEM NUMBER:
March 17, 2015 4.1
SUBJECT:
2014 Electric Reliability Report(Revised)
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:
After Last month's report of our reliability numbers, it was brought to our attention that some of
the outages reported to the American Public Power Association(APPA)had the wrong customer
count in them. After sending them the corrected data, some of our reliability numbers changed,
although our CAIDI number stayed close to the same. I have attached APPA's eReliability
Tracker 2014 Annual Report. Even though the primary uses of reliability statistics are for self-
evaluation,utilities can use these statistics to compare with data from similar utilities. I was
unable to get MMUA's comparisons because other municipals were unwilling to share their
results.
In 2014, 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
from 2005 through 2014.
Year # of Customers # of Outage Minutes #of Outages
2005 8398 558,140 59
2006 8804 314,510 73
2007 9163 67,845 47
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2008 9067 155,768 57
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
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
2013 and 2014 statistics. Also included are APPA's 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 (ASA!)
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 2014 ASAI is 99.9945%Availability ERMU's 2013 ASAI was 99.999%Availability
Our utility's ASAI: 99.9945
Average ASAI for Utilities Within our Region 99.9894
Average ASAI for Utilities Within our Customer Size Class 99.9834
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
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 2014 CAIDI is 199.883 minutes ERMU's 2013 CAIDI was 118.23 minutes
Our utility's CAIDI: 199.8838
Average CAIDI for Utilities Within our Region 95.2256
Average CAIDI for Utilities Within our Customer Size Class 107.7752
System Average Interruption Duration Index(SAID!)
SAIDI is defined as the average interruption duration for customers served during a specified time
period. It is determined by summing the customer minutes off for each interruption during a specified
time period and dividing that sum by the average number of customers served during that period. The
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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 2014 SAIDI is 28.54 minutes ERMU's 2013 SAIDI was 5.97 minutes
Our utility's SAIDI: 28.54
Average SAIDI for Utilities Within our Region 55.49
Average SAIDI for Utilities Within our Customer Size Class 87.14
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 customers interrupted in a time period by the
average number of customers served. The resulting unit is"interruptions per customer."
ERMU's 2014 SAIFI is 0.1428 ERMU's 2013 SAIFI was 0.0505
Our utility's SAIFI: 0.143
Average SAIFI for Utilities Within our Region 0.817
Average SAIFI for Utilities Within Your Customer Size Class 0.839
Another statistic staff gets concerned about is the average length of any outage. Elk River
Municipal Utilities' 2014 average length of outage was 131.07 minutes. In 2013 the average
length of outage was 116.84 minutes. Electric utilities with a high percentage of underground
facilities will exhibit higher length of outage time than electric utilities with more overhead
facilities.
Staff reviews these statistics in detail to find ways to continually improve our system. These
statistics are very good compared to other utilities. In 2014,birds and animals caused the greatest
number of outages resulting in 31.25%of our outage incidents. Outages resulting from branches
and/or trees made up 2.08% of our outage incidents. This low percentage is a reflection of the
good tree trimming our crews do during the winter. Other contributing factors include:
underground faults 16.67%; dig-ins, etc. 6.25%; component failure 4.17%; transformer failure
4.17%; fuse failure 10.42%; connector failure 12.50%; vehicle vs. pole 10.42%; and weather
related outages accounted for 2.08%of the incidents.
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 2014. Overall, our electric
distribution system is robust and our reliability is very high.
ACTION REQUESTED:
No action is required.
ATTACHMENT:
• American Public Power Association's eReliablity Tracker 2014 Annual Report
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eReliabiltly'facker..
•
2014 Annual Report
Elk River Municipal Utilities
The eReliability Tracker Annual Report was created by the American Public Power 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's system. The data used to generate
this report reflect activity in the eReliability Tracker from January 1, 2014 to December 31, 2014. 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 for your utility as of February 24, 2015; therefore, any
changes made after that date are not represented in this report.
I. General Overview
Reliability reflects historic and ongoing engineering investment decisions within a utility. Proper use of
reliability metrics ensures that the 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. All utilities are equally
weighted and all 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 2014. 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 approximately
17,606 outages from 143 utilities, that recorded more than two outages for 2014 during the time period of
analysis.
52
To limit the comparison of utilities of truly different sizes, this report separates utilities into groups
according to their number of customers served. In Table 1, the customer size distribution of utilities that
use the eReliability Tracker is split into fifths to create five distinct customer size classes.
Since the utilities considered in this report represent a wide variety of locations across the United States,
each utility is grouped with all others located in their corresponding APPA region. Figure 1 shows the
number of utilities using the eReliability Tracker in each APPA region and Figure 2 displays the current
United States map of APPA regional divisions.
Your utility belongs to customer size class 3 and region 3.
Table 1
Customer size range per customer size class
Class 1: 0-3,600
Class 2: 3,600-6,265
Class 3: 6,265- 10,220
Class 4: 10,220-20,364
Class 5: 20,364- 1,481,735
Figure 1
Number of eRT utilities per APPA region
60 - 50
m 50 - 42
}, 40 - 32
z, 30 24 17
20 - 13 12 10
A 1 0 - 9 II . 2
0
1 2 3 4 5 6 7 8 9 10
APPA Region
Figure 2
Map of APPA Regions as of January 1, 2014
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53
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 bare 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 to create an outage in the system:
-Total number of customers served on the day of the outage
-Time and date when the outage began
-Primary cause of outage
-Address where the outage was located
It is important to note that the time when the outage ended is not required in case the outage is ongoing;
therefore, outages without end dates at the time of the report analysis are not included in the indices that
measure duration, such as SAIDI and CAIDI. However, they are included in the calculations measuring
interruption frequencies, such as SAIFI or MAIFI, as well as in the analysis of outage causes.
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
APPA 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. The threshold takes into account the utility's past outage history up to 10 years in
order to make this calculation. 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 major event threshold is (minutes).
If you wish to remove major events, the threshold calculated above is important to note because it impacts
your SAIDI analysis. For the next year, based on your utility's outage history, any event with a SAIDI
greater than minutes is considered as a major event and can be removed in your
analysis.
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
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.
3
54
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.
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: 28.5464 28.5464 28.5464 0
Average eReliability Tracker Utility SAIDI 111.6347 67.8888 105.3348 6.2962
Average SAIDI for Utilities Within Your Region 55.4969 34.7555 52.7954 2.7015
Average SAIDI for Utilities Within Your Customer Size Class 87.1486 47.955 83.5351 3.6156
Table 3
Summary statistics of the SAIDI data compiled from the eReliability Tracker
All No MEs Unscheduled Scheduled
Minimum Value 0.2461 0.2461 0.2461 0
First Quartile(25th percentile) 18.6824 11.2111 18.6751 0
Median Quartile (50th percentile) 50.4729 25.1516 47.6868 0.0146
Third Quartile (75th percentile) 97.2444 56.433 91.815 0.701
Maximum Value 3128.437 3128.437 2974.7748 308.3812
Figure 3
Average SAIDI for all utilities that use the eReliability Tracker per region
300 - 281.861
m 250 -
c
E 200 - 175.5715
0
150 -
a 102.863 101.8402 107.5171 92.1373
E$ 100 -
cp 64.6299 55.4969
50 - 41.2235
1 2 3 4 5 6 7 8 9 10
APPA Regions
4
55
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 .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: 0.1428
Average eReliability Tracker Utility SAIFI 0.9615
Average SAIFI for Utilities Within Your Region 0.817
Average SAIFI for Utilities Within Your Customer Size Class 0.8387
Table 5
Summary statistics of the SAIFI data compiled from the eReliability Tracker
Minimum Value 0.0019
First Quartile (25th percentile) 0.3184
Median Quartile (50th percentile) 0.621
Third Quartile(75th percentile) 1.0821
Maximum Value 20
Figure 4
Average SAIFI for all utilities that use the eReliability Tracker per region
1.8
1.6 - 1.5575
1.411
1.4 -
1.2 - 1.0836 1.0366
0.9556
a, 1 0.817 0.7453
co
0.8 0.5899 II
¢ 0.6 - 0.3925
0.4 -
0.2 - . 0
1 2 3 4 5 6 7 8 9 10
APPA Regions
5
56
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: 199.8838
Average eReliability Tracker Utility CAIDI 108.8292
Average CAIDI for Utilities Within Your Region 95.2256
Average CAIDI for Utilities Within Your Customer Size Class 107.7752
Table 7
Summary statistics of the CAIDI data compiled from the eReliability Tracker
Minimum Value 17.2115
First Quartile(25th percentile) 60.0165
Median Quartile (50th percentile) 82.1022
Third Quartile(75th percentile) 132.3397
Maximum Value 782.4045
Figure 5
Average CAIDI for all utilities that use the eReliability Tracker per region
180 - 162.7736
• 160 - 149.5293
133.5417
140 -
c
'E 120 - 102.9167
O 100 - 94.0484 95.2256 93.3338 87.2413
74.8117
U 80
a) 60 -
m
> 40 -
20 - 0
1 2 3 4 5 6 7 8 9 10
APPA Regions
6
57
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 below.
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: 0.0001
Average eReliability Tracker Utility MAIFI 0.463
Average MAIFI for Utilities Within Your Region 0.7759
Average MAIFI for Utilities Within Your Customer Size Class 0.3692
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) 0.1539
Maximum Value 12.7241
Figure 6
Average MAIFI for all utilities that use the eReliability Tracker per region
1 -
0.9 0.8642
.9
0.7759
0.8 -
Q 0.7 - 0.6227
2 0.6 - 0.506
a) 0.5 - 0.4083
m 0.4
¢' 0. - 0.1877 0.209
0. 0
1 2 3 4 5 6 7 8 9 10
APPA Regions
7
58
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.
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 (%): 99.994568
Average eReliability Tracker Utility ASAI 99.979141
Average ASAI for Utilities Within Your Region 99.989441
Average ASAI for Utilities Within Your Customer Size Class 99.98347
Table 11
Summary statistics of the ASAI data compiled from the eReliability Tracker
Minimum Value 99.404787
First Quartile (25th percentile) 99.981498
Median Quartile (50th percentile) 99.990397
Third Quartile(75th percentile) 99.996445
Maximum Value 99.999953
Figure 7
Average ASAI for all utilities that use the eReliability Tracker per region
100 - 99.992156
99.987703 99.989441
99.99 - 99.980429 99.980624 99.979543 99.98247
99.98 -
99.966655
Q 99.97 -
m
m 99.96 - 99.953908
¢ 99.95 -
99.94 -
99.93
1 2 3 4 5 6 7 8 9 10
APPA Regions
8
59
2013 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 requesting reliability statistics in
their survey from utility participants; therefore, APPA 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 is based on 2013 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.
There were approximately 965 utilities that submitted reliability data to the EIA. 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 APPA'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:
Table 12
Summary statistics of the SAIDI data compiled from 2013 data collected by EIA
IEEE Method Other Method
All No MEDs All No MEDs
Average 249.4246 139.3246 210.5557 136.5727
Minimum Value 0.0000 0.0000 0.0000 0.0000
First Quartile (25th percentile) 53.5000 42.0000 20.0000 6.0000
Median Quartile(50th percentile) 128.0000 88.0000 71.0000 50.5000
Third Quartile (75th percentile) 249.5000 145.0250 169.0000 112.0000
Maximum Value 10,983.0000 10,983.0000 12,944.0000 10,726.0000
Table 13
Summary statistics of the SAIFI data compiled from 2013 data collected by EIA
IEEE Method Other Method
All No MEDs All No MEDs
Average 15.2657 13.5847 2.5339 4.1404
Minimum Value 0.0000 0.0000 0.0000 0.0000
First Quartile(25th percentile) 0.8400 0.6778 0.3443 0.1818
Median Quartile (50th percentile) 1.2300 1.0000 1.0000 0.7695
Third Quartile(75th percentile) 2.0000 1.6150 1.9455 1.3925
Maximum Value 2,837.0000 2,335.0000 87.0000 674.0000
9
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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
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 will have a large number of outages compared to a
small utility; in order to not have the collective information be more representative of the large utility, the
number of 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
2013.
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.
10
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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 System 2
2.5 - 2.1579
a 2 -
`0 1.4197 1.4116
a) 1.5 -
c 1.0882 0.9371
m 1 -
U
O 0.5 -
0 1 1 1 1 I
Tree Squirrel Equipment Unknown Electrical Failure
Outage Causes Types
Figure 9
Top five customer-weighted causes of sustained outages for your utility
1.4 1.2731
0, 1.2
ID
co 1
rY
m 0.8 0.6365
ET?0.6 0.5304
0.4244
:1 0.4
0.3183
U
O 0.2
0
Squirrel Vehicle Accident Electrical Failure Wildlife Equipment Damage
Outage Cause Types
Figure 10 2
Top five customer-weighted occurrence rates for sustained outage causes in your region
2 1.7031
m 1.5 1.3537
1.2082 1.1305 1.1208
c• 1
0° 0.5
0
0
Wildlife Squirrel Natural Equipment Weather
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.
11
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it
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 their 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. Utilities with less than
eight momentary outages recorded in the eReliability Tracker as of January 27, 2014 are not included in
the following analysis of momentary outage causes. 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 System 2
0.18 - 0.1695
0.16 -
0.14 -
c 0.12 -
0.1 -
2 0.08 -
c 0.06 -
0.0345 0.0345 0.0333 0.0305
o 0.04 -
0.02 -
0 _
Unknown Squirrel Storm Weather Natural
Outage Cause Types
Figure 12
Top five customer-weighted causes of momentary outages for your utility'3
0.12 - 0.1061
0) 0.1 -
cts
0.08 -
N
m 0.06 -
E
c:, 0.04 -
0
0.02 -
0 0 0 0
0
Contractor-Dig-In None 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.
12
63
Figure 13
2
Top five customer-weighted occurrence rates for momentary outage causes in your region
0.6 -
0.5046
u, 0.5 -
a)
E2 0.4 -
m
c 0.3 -
2
U 0.2 - 0.1553 0.1407 0.1262 0.1262
o
0 0.1 -
0
Unknown Repairs Storm Natural Utility Human Error
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:
Tanzina Islam
Energy and Environmental Specialist
TIslam @PublicPower.org
202.467.2961
Alex Hofmann
Director, Energy and Environmental Services
AHofmann @PublicPower.org
202.467.2956
Michael J. Hyland
Senior Vice President, Engineering Services
MHyland @PublicPower.org
202.467.2986
The eReliability Tracker was funded by a grant from the Demonstration of Energy& Efficiency
DEED' Developments (DEED) Program.
'rte ° American
A
Public Power Copyright 2015 by the American Public Power Association. All rights
��a Association reserved.
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