2019-059 2018 APPA Reliability AwardDate: March 29, 2019 Report No. 2019-059
INFORMAL STAFF REPORT
TO MAYOR AND CITY COUNCIL
SUBJECT:
Denton Municipal Electric Receives 2018 APPA Reliability Award
PURPOSE:
The purpose of this Informal Staff Report is to provide a high-level summary of Denton
Municipal Electric’s recent award given by the American Public Power Association (APPA) for
achieving Excellence in Reliability for 2018. This award is given to APPA participating utilities
who are in the top quartile compared to data collected by the United States Energy Information
Administration (EIA). As a collaborative piece with this award, the APPA has provided Denton
Municipal Electric’s 2018 Annual Benchmarking Report which is generated from data input into
eReliability and from the EIA.
DISCUSSION:
The EIA collects, analyzes, and disseminates independent and impartial energy information to
promote sound policymaking, efficient markets, and public understanding of energy and its
interaction with the economy and environment. One of the many databases maintained by this
organization records reliability data reported by electric utilities through submittal of Form EIA-
861 – Annual Electric Power Industry Report.
Denton Municipal Electric (DME) participants in the APPA’s eReliability program.
“eReliability” is a web-based service that collects, categorizes, and summarizes outage data for
460 participating public power utilities. However, only 277 utilities are included in the analysis
based on those utilities who verified their data and experienced two or more outages in 2018.
The complete 2018 Annual Benchmarking Report, which is attached to this ISR, provides the
computed values of key indices for DME as well as comparisons to 1) eReliability data, 2)
utilities in the associated region (Region 4) that DME is included within, and 3) comparisons
with utilities of similar customer size. Items 2 and 3 are extracted from the Annual Electric
Power Industry report.
There are five (5) key indices used to track how an electric utility is performing in relation to
reliability. These indices (along with their definitions), as well as DME’s ranking compared to
average eReliability in input, Region 4, and finally to utilities with the same customer size:
System Average Interruption Duration Index (SAIDI): average interruption duration
(in minutes) for customers served by a utility system during a specific time period.
DME SAIDI 56.20
Average eReliability SAIDI 202.45
SAIDI for Utilities in Region 4 767.77
SAIDI for Utilities of the same Customer Size 213.61
Date: March 29, 2019 Report No. 2019-059
System Average Interruption Frequency Index (SAIFI): average number of instances
a customer on the utility system will experience an interruption during a specific time
period.
DME SAIFI 0.832
Average eReliability SAIFI 0.954
SAIFI for Utilities in Region 4 0.653
SAIFI for Utilities of the same Customer Size 1.0829
Customer Average Interruption Duration Index (CAIDI): average duration (in
minutes) of an interruption by customers during a specific time frame.
DME CAIDI 67.58
Average eReliability CAIDI 180.75
CAIDI for Utilities in Region 4 733.11
CAIDI for Utilities of the same Customer Size 139.73
Momentary Average Interruption Frequency Index (MAIFI): average number of
times a customer of the utility system will experience a momentary interruption.
DME MAIFI 0.0544
Average eReliability MAIFI 0.2938
MAIFI for Utilities in Region 4 0.1108
MAIFI for Utilities of the same Customer Size 0.4612
Average Service Availability Index (ASAI): a measure of the average availability of the
sub-transmission and distribution system that serve customers.
DME ASAI 99.99%
Average eReliability ASAI 99.96%
ASAI for Utilities in Region 4 99.85%
ASAI for Utilities of the same Customer Size 99.96%
A review of DME for all of the indexes, when compared to eReliability, Region 4, and of
other utilities of the same customer size show DME’s performance is rated higher for
ALL values in every ranking with the one exception of SAIFI for utilities in Region 4.
CONCLUDING REMARKS:
DME’s engineering and operational staff place a high degree of importance in its delivery of
service to the citizens of Denton, Texas. This service is provided through several proactive
actions.
Tree trimming.
Feeder sweeps.
Date: March 29, 2019 Report No. 2019-059
Planned/Scheduled outages including comprehensive communications with customers
who may be affected.
For unplanned outages, commitment to restoration deployment – even after normal
workhours. Restoration target of thirty-minutes or less when DME is on site.
System planning and design that accounts for service contingencies to restore power to as
many customers as possible while enabling isolating damaged area(s).
Continual monitoring of system expansion and loading to detect potentially weak
components.
Flexibility to adjust required actions to facilitate restoration.
24/7/365 System Operations to respond to outages in real time.
These actions, plus more, have shown to be beneficial to Denton in the prevention or response to
incidents that have the potential to lessen service. The value and importance of these actions can
be quantified as was shown in the award and benchmarking report.
ATTACHMENTS:
1. Certificate presented to DME by APPA
2. Denton Municipal Electric 2018 Annual Report 6065
STAFF CONTACT:
Jerry Fielder, P.E.
Division Engineering Manager, DME
(940) 349-7173
jerry.fielder@cityofdenton.com
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.
Denton Municipal Electric
I. General Overview
Funded by a grant from the Demonstration of Energy & Efficiency Developments (DEED) Program, the
eReliability Tracker Annual Report was created by the American Public Power Association (the
Association) to assist utilities in their efforts to understand and analyze their electric system. This report
focuses on distribution system reliability across the country and is customized to each utility. The data
used to generate this report reflect activity in the eReliability Tracker from January 1, 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.
2
27
129
94
16
66
13
41
60
13 0
0
20
40
60
80
100
120
140
1 2 3 4 5 6 7 8 9 10Association RegionCount of Utilities .Table 1
Customer size range per customer size class
Figure 1
Number of eReliability Tracker utilities per Association region
Your utility belongs to customer size class and region .5 4
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.
Class 1
Class 2
Class 3
Class 4
Class 5
0 -1,337
1,338 - 3,003
3,004 - 6,679
12,263 - 650,000
6,680 - 12,262
Figure 2
Association map of regions
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.
3
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 (minutes).0
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.
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.
1
1
4
Your utility's SAIDI 56.199
234.8737
126.5944 133.1295
767.7695
315.8426 275.3225
103.0168
174.2614 141.5934
0
100
200
300
400
500
600
700
800
900
1 2 3 4 5 6 7 8 9 10
Association RegionsAverage SAIDI (minutes) . Average eReliability Tracker SAIDI 202.449
Average SAIDI for Utilities Within Your Region 767.7695
Average SAIDI for Utilities Within Your Customer Size Class 213.6104
Minimum Value 0.283
First Quartile (25th percentile)21.647
Third Quartile (75th percentile)141.0617
Median Quartile (50th percentile)53.2225
Maximum Value 8746.1
Figure 3
Average SAIDI for all utilities that use the eReliability Tracker per region
System Average Interruption Duration Index (SAIDI)
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.
5.963
17.463
1.5023
3.2353
50.229
185.0572
766.4678
210.4273
0.186
19.69
52.313
131.51
8743.182
0
0
0.134
2.086
1580.062
Unscheduled ScheduledAll
Unscheduled ScheduledAll
Table 3
Summary statistics of the SAIDI data compiled from the eReliability Tracker
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
56.199
69.0185
27.2098
55.1267
No MEs
0.283
12.203
27.084
63.238
1843.61
No MEs
SAIDI is defined as the average interruption duration (in minutes) for customers served by the utility
system during a specific time period.
5
Your utility's SAIFI 0.832
1.1986
0.881
0.6658 0.6529
1.3146 1.3898
1.0079 1.0152
0.7024
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1 2 3 4 5 6 7 8 9 10
Association RegionsAverage SAIFI (Interruptions) . Average eReliability Tracker SAIFI 0.9541
Average SAIFI for Utilities Within Your Region 0.6529
Average SAIFI for Utilities Within Your Customer Size Class 1.0829
Minimum Value 0.0071
First Quartile (25th percentile)0.284
Third Quartile (75th percentile)1.223
Median Quartile (50th percentile)0.667
Maximum Value 7.535
Figure 4
Average SAIFI for all utilities that use the eReliability Tracker per region
System Average Interruption Frequency Index (SAIFI)
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 5
Summary statistics of the SAIFI data compiled from the eReliability Tracker
Table 4
Average SAIFI for all utilities that use the eReliability Tracker, belong to your region, and are
grouped in your customer size class
SAIFI is defined as the average number of instances a customer on the utility system will experience an
interruption during a specific time period.
6
122.2303 179.4855 173.9667
733.1139
149.4425 177.7918
104.9817 138.1305 181.1176
0
100
200
300
400
500
600
700
800
1 2 3 4 5 6 7 8 9 10
Association RegionsAverage CAIDI (minutes) .Figure 5
Average CAIDI for all utilities that use the eReliability Tracker per region
Customer Average Interruption Duration Index (CAIDI)
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.
Your utility's CAIDI 67.581
Average eReliability Tracker CAIDI 180.7475
Average CAIDI for Utilities Within Your Region 733.1139
Average CAIDI for Utilities Within Your Customer Size Class 139.7256
Minimum Value 10.413
First Quartile (25th percentile)60.692
Third Quartile (75th percentile)137.545
Median Quartile (50th percentile)86.822
Maximum Value 7981.064
Table 6
Average CAIDI for all utilities that use the eReliability Tracker, belong to your region, and are
grouped in your customer size class
Table 7
Summary statistics of the CAIDI data compiled from the eReliability Tracker
CAIDI is defined as the average duration (in minutes) of an interruption experienced by customers during
a specific time frame.
7
Your utility's MAIFI 0.0544
0.2366 0.1888
0.3142
0.1108
0.2214
0.3169 0.3746
0.7016
0.0447
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
1 2 3 4 5 6 7 8 9 10
Association RegionsAverage MAIFI (Interruptions) .Average eReliability Tracker MAIFI 0.2938
Average MAIFI for Utilities Within Your Region 0.1108
Average MAIFI for Utilities Within Your Customer Size Class 0.4612
Minimum Value 0
First Quartile (25th percentile)0
Third Quartile (75th percentile)0.143
Median Quartile (50th percentile)0
Maximum Value 7.687
Figure 6
Average MAIFI for all utilities that use the eReliability Tracker per region
Momentary Average Interruption Frequency Index (MAIFI)
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 9
Summary statistics of the MAIFI data compiled from the eReliability Tracker
Table 8
Average MAIFI for all utilities that use the eReliability Tracker, belong to your region, and are
grouped in your customer size class
MAIFI is defined as the average number of times a customer on the utility system will experience a
momentary interruption.
8
Your utility's ASAI (%)99.9892
99.9554 99.9758 99.9747 99.8538 99.9399 99.9475 99.9803 99.9668 99.9742
0.00
20.00
40.00
60.00
80.00
100.00
120.00
1 2 3 4 5 6 7 8 9 10
Association RegionsAverage ASAI (%) .Average eReliability Tracker ASAI 99.9615
Average ASAI for Utilities Within Your Region 99.8538
Average ASAI for Utilities Within Your Customer Size Class 99.9595
Minimum Value 98.3359
First Quartile (25th percentile)99.9731
Third Quartile (75th percentile)99.9961
Median Quartile (50th percentile)99.9899
Maximum Value 99.9999
Figure 7
Average ASAI for all utilities that use the eReliability Tracker per region
Average Service Availability Index (ASAI)
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 11
Summary statistics of the ASAI data compiled from the eReliability Tracker
Table 10
Average ASAI for all utilities that use the eReliability Tracker, belong to your region, and are
grouped in your customer size class
ASAI is defined as a measure of the average availability of the sub-transmission and distribution systems
that serve customers.
9
2018 Energy Information Administration (EIA) Form 861 Data
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 13
Summary statistics of the SAIFI data collected in 2017 and published in 2018 by EIA
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.
Table 12
Summary statistics of the SAIDI data collected in 2017 and published in 2018 by EIA
All No MEDs All No MEDs
IEEE Method Other Method
All No MEDs All No MEDs
IEEE Method Other Method
134.5683
Minimum Value
First Quartile (25th percentile)
Third Quartile (75th percentile)
Median Quartile (50th percentile)
Maximum Value
Average 377.6190 132.7504383.0213
0.00000.2750 0.00000.3000
55.441083.2050 27.587341.5000
94.9580169.6020 78.0145102.2580
161.9000321.0500 150.7025247.5543
2796.187016472.0710 2796.187017182.0000
1.3091
Minimum Value
First Quartile (25th percentile)
Third Quartile (75th percentile)
Median Quartile (50th percentile)
Maximum Value
Average 1.7178 1.06281.4603
0.00000.0030 0.00000.0040
0.69000.9000 0.39400.5770
1.08701.3700 0.83701.0090
1.52002.0010 1.45451.8930
55.441083.2050 9.048012.8000
10
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.
Table 14
Analysis of overhead miles of line and interruptions
Interruptions per Mile Customers per Mile
Average for eReliability Tracker Utilities
Average for Utilities Within Your Region
Your Utility
Your utility's overhead miles of line as reported by Platts: 326.27
1.8634 146.3174
0.984 100.745
1.3212 89.4375
Table 15
Analysis of underground miles of line and interruptions
Interruptions per Mile Customers per Mile
Average for eReliability Tracker Utilities
Average for Utilities Within Your Region
Your Utility
Your utility's underground miles of line as reported by Platts: 417.29
1.457 114.402453928922
8.6341 613.4802
8.4568 703.6838
Minutes per Mile
177.427
186
732.4471
Minutes per Mile
138.7263
1340
2460.5585
11
III. 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.
Sustained 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.
12
1.5185
0.9466 0.8061
0.3712 0.2575
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Outage Cause TypesOccurrence Rates .Figure 9
Top five customer-weighted causes of sustained outages for your utility
Figure 10
Top five customer-weighted occurrence rates for sustained outage causes in your region
2.2993
1.7616 1.743
1.3536
0.9642
0
0.5
1
1.5
2
2.5
Outage Cause TypesOccurrence Rates .Equipment
Replacement
Squirrel Electrical Failure Equipment Worn
Out
Lightning-Induced
Flashover
2
2
Utility Maintenance
and Repairs
Equipment Squirrel Equipment
Replacement
Equipment Worn Out
Figure 8
Top five customer-weighted occurrence rates for common causes of sustained outages for all
utilities that use the eReliability Tracker Service
1.2194
0.4641 0.3473 0.3259 0.2944
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Trees Human Weather Squirrel Unknown
Outage Causes TypesOccurrence Rates .2
Tree Equipment Electrical Failure Squirrel Utility Maintenance
and Repairs
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.
2
13
0.0186 0.0186 0.0186 0.0186
0.0185
0.01844
0.01846
0.01848
0.0185
0.01852
0.01854
0.01856
0.01858
0.0186
0.01862
Outage Cause TypesOccurrence Rates .0.1321
0.0904 0.0812
0.0633 0.0598
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
Trees Human Weather Squirrel Unknown
Outage Cause Types Occurrence Rates .Momentary Outage Causes
Figure 11
Top five customer-weighted occurrence rates for common causes of momentary outages for all
utilities that use the eReliability Tracker Service
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.
2
Utility Maintenance and
Repairs
Unknown Equipment Replacement Failure of Greater
Transmission
Equipment
Figure 12
Top five customer-weighted causes of momentary outages for your utility2, 3
Storm Operations Wind Equipment
Replacement
Unknown
If your utility has less than eight momentary outages recorded in the eReliability Tracker, this graph will be blank.3
14
0.1404
0.1103
0.0234
0.0066 0.0033
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
Outage Cause TypesOccurrence Rates .Figure 13
Top five customer-weighted occurrence rates for momentary outage causes in your region2
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:
Lightning Storm Weather Power Supply Squirrel
Copyright 2019 by the American Public Power Association. All rights reserved.
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
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