5.2 ERMUSR 04-08-20254r.;,
Elk Riv
Municipal Utilities UTILITIES COMMISSION MEETING
TO:
FROM:
ERMU Commission
Mike Tietz— Technical Services Superintendent
MEETING DATE:
AGENDA ITEM NUMBER:
April 8, 2025
5.2
SUBJECT:
2024 Annual Reliability Report
ACTION REQUESTED:
Receive the 2024 Annual Reliability Report
BACKGROUND:
Minnesota Rules Chapter 7826 Public Utilities Commission Electric Utility Standards cover
safety, reliability, service, and reporting requirements. Per 7826.0100(A), municipal utilities are
exempt from these requirements. However, the Elk River Municipal Utilities Commission
adopted several parts of this chapter as a Distribution Reliability Standard policy requiring
annual reporting on system reliability.
DISCUSSION:
In 2024, our reliability index numbers remained impressive. These reliability index numbers
demonstrate the condition of our solidly built electrical system as well as the excellent response
times our line crews provide. The utility's commitment to accountability, long term visioning of
system design, and ongoing system maintenance are also reflected by these numbers.
The table below reflects the number of customer outage minutes for the last 10 years.
Year
# of Customers
# of Outage Minutes
# of Outages
2015
9449
225,337
41
2016
10862
432,310
59
2017
11489
354,625
40
2018
12158
117,055
51
2019
12463
312,885*
59
2020
12604
197,884
51
2021
13038
628,670
61
2022
13228
174,500
50
2023
13543
187,469
51
2024
13797
575,509
43
*118,978 of these minutes are due to two separate transmission outages.
Page 1 of 3
170
Listed below are several reliability indices that are used within the electric industry to make it
easier to compare performance among utilities along with ERMU's 2023 and 2024 statistics.
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 2024 ASAI is 99.992% Availability ERMU's 2023 ASAI is 99.9973% 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 2024 CAIDI is 118.931 minutes ERMU's 2023 CAIDI is 84.827 minutes
System Average Interruption Duration Index (SAIDI)
SAIDI is defined as the average interruption duration (in minutes) for customers served
during a specified time period. It is determined by summing the customer minutes off for each
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 2024 SAIDI is 42.083 minutes ERMU's 2023 SAIDI was 14.077 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 2024 SAIFI is 0.354 ERMU's 2023 SAIFI was 0.166
' Only outages lasting longer than five minutes are included in the calculations, as defined by IEEE 1366.
Page 2 of 3
171
Staff review these statistics in detail to find ways to continually improve our system. These
statistics are very good when compared with other utilities. As indicated by the following pie
chart and statistics list, you can see the causes of the outages experienced in 2024.
Other Outage Cause
Count
View
12%
16
0
Bird
2%
Squirrel
11
0
Overhead
2%
Vehicle Accident
4
m
Wildlife
Tree
5%
37% Equipment
3
m
Wildlife
2
0
Equipment
Overhead
1
m
7%
_
Bird
1
0
Non -Utility Excavation
1
0
Vehide Accident
Underground
1
0
9%
Lightning
1
0
Wind
1
0
Utility Human Error
1
0
Squirrel
2696 Total
43
Many investor -owned and cooperative run utilities "storm normalize "their reliability numbers
by removing "major outages" due to storms from their reliability index number calculations.
Our reliability numbers have not been storm normalized. Our numbers reflect these major
outages and represent what our customers experienced in 2024. Overall, our electric
distribution system is very resilient, and our system reliability remains excellent.
Please receive the attached American Public Power Association's (APPA) eReliability Annual
Report which contains published averages that can be used to better understand the
performance of our electric system relative to other utilities nationally and to those within their
region or size class.
ACTION REQUESTED:
Staff requests the Commission receive and file the APPA eReliability Tracker 2024 Annual
Report for Elk River Municipal Utilities.
ATTACHMENT:
• APPA eReliability Tracker 2024 Annual Report for Elk River Municipal Utilities
Page 3 of 3
172
%n(-l)-q
Elk River Municipal Utilities
'* ANNUAL
0 BENCHMARKING
N REPORTTRR""BKER
American Public Power Association
A M E R I CA N
DErljPUBLIC
W.-E .
RESEARCH & DEVELOPMENT
ASSOCIATION
Powering strong communities
173
I. About This Report
This report focuses on distribution system reliability across the country and is customized to
each utility that participates in the American Public Power Association's eReliability Tracker
f etvitm. APPA created the eReliability Tracker Annual Report to assist utilities in their e
understand and analyze their electric system. In 2012, APPA developed the eReliability Tracker
fftffm*De\aetppntEfntOD15E[)emonstration of Energy & E
program.
Ebds dz0a time eReliability Tracker from January 1, 2024 to December 31, 2024
EbO�youalytil togibb gsriifgedyde not have a full year of
data in the system. The report includes data recorded as of February 25, 2025.
fledsalbdttylnestoric and ongoing engineering investment decisions within a utility.
Proper use of reliability metrics ensures that a utility is performing its intended function and is
ffctivildringrseev.ice in a consistent and e
While the primary use of reliability statistics is for self -evaluation, you can use these statistics
ff6armQ�a�ar�lycsralt�}i�c�liiiir utilities. However, di
fiamation, 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 improve comparative analyses by grouping
utilities by size and region.
Since this report contains data for all utilities that use the eReliability Tracker, it is important to
€fatiE;bJBphwM ticbWidyidar�ae3sEmall utility can a
the issues associated with comparability, each utility's reliability statistics are weighted based
on customer count when aggregated. This means that all utilities are equally weighted, and all
individual statistics are developed on a per customer basis.
EHERRO@4regate statistics in this report are calculated from the 350 utilities with veri
outage data. Utilities that experienced no outages in 2024, or did not upload any data, will
6altd,vD�eetia�rir`i@I'udas� in their report for utility-speci
the aggregate analysis. Also note that log -normal data with a z-scoreM greater than 3.25 may
i<y Widt&1f ith9j jgregate statistics.
f*� kaFec me: mnd atfeartiostxnoebmzsiolorpaifiBa5 indicates that the data point
is three and one -quarter standard deviations from the mean. A z-score of 0 indicates that the data point is identical to the mean.
174
dd1hyClassi
This report separates utilities into groups according to geographic region and the number of
customers served. Table 1 shows the range of customer counts for utilities that use the
>iilRdiaM4gTrnmaoerobppproximately 107 utilities per group.
Your utility is in size class bnd region 3
Table 1. Customer count range per size class
Customer Count Range
Class 1
>0
Class 2
>1,527
Class 3
>3,582
Class 41 >7,526
Class 5 >14,528
Each utility is also grouped with all other participating utilities within their region. Figure 1
shows the number of utilities using the eReliability Tracker in each region and Figure 2 shows
the states and territories included in each region.
Figure 1. Number of utilities subscribed to the eReliability Tracker by region
140
120
Ln
N
4- 100
L
4
80
-
O
(U 60
E
Z) 40
Z
20
0
Regions
175
Figure 2. Regions
r-
AMERICAN GUAM NORTHERN PUERTO U.S. VIRGIN
SAMOA MARIANA RICO ISLANDS
ISLANDS
REGION 8
176
II. IEEE Statistics
I imithmtnet;i=ee1iability, the industry standard metrics are de
Electrical and Electronics Engineers' Guide for Electric Power Distribution Reliability Indices, or
IEEE 1366 guidelines. For each 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).
It is important to note how major events (MEs) are calculated and used in this report. An
example of an ME includes severe weather, such as a tornado or hurricane, that leads to
unusually long outages in comparison to your distribution system's typical outage. This report
uses the A9113hAlVdium ftildctly on the SAIDI for speci
rather than a daily SAIDI. The APPA ME threshold allows a utility to remove outages that
exceed the IEEE 2.5 beta threshold for outage events, which considers up to 10 years of the
utility's outage history. In the eReliability Tracker, if a utility does not have at least 36 outage
events prior to the year being analyzed, then no threshold is calculated. If this is the case for
OWiatudilfbft tiabul,,ectiomlh idveutNULL value in the following
MEs in the SAIDI, SAIFI, CAIDI, and ASAI sections 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.
VvA&dtifity's APPA major event threshold is
For each of the reliability indices, this report displays your utility's metrics alongside the mean
values for all utilities using the eReliability Tracker and within the same class and region as
gk=btdivyi.tft-eeach of the following subsections allows you to better
understand the performance of your electric system relative to other utilities nationwide and
to those within your same region or size class. The second table breaks down the national
data into quartile ranges, a minimum value, and a maximum value.
All indices, except MAIFI, are calculated for outages with and without MEs. Furthermore, the
tables show indices for scheduled and unscheduled outages. Note that scheduled and
unscheduled calculations include MEs. Also note that wherever MEs are excluded, the
exclusion is based on the APPA ME threshold for your system.
177
II.1. System Average Interruption Duration Index
SAIDI is the average duration (in minutes) of an interruption per customer served by the utility
f NffiMfrwpeci
&rrrdrSM(E9 is a sustained interruption index, only outages lasting longer than
are included in the calculations. SAIDI is calculated by dividing the sum of all customer
minutes of interruptioni2�SdittlirinafronpaLby the average number of
customers served during that period. For example, a utility with 100 customer minutes of
interruption and 100 customers would have a SAIDI of 1.
Note that in the tables below, scheduled and unscheduled calculations include MEs. Also note
that wherever MEs are excluded, the exclusion is based on the APPA ME threshold for your
system.
T&Wmg.e SAIDI with and without MEs
In minutes
All
No MEs
Unscheduled
Scheduled
Your utility
42.08
9.8
42.08
NULL
Utilities that use the eReliability Tracker
120.3
54.49
113.49
13.19
Utilities in your region
50.0
32.24
48.83
3.0
Utilities in your size class
96.25
39.74
93.5
4.31
16abteT3ary SAIDI data from the eReliability Tracker
In minutes
All
No MEs
Unscheduled
Scheduled
Minimum
0.08
0.08
0.08
<0.01
First Quartile
19.39
11.07
18.77
0.19
Median
44.37
26.79
40.95
1.24
Third Quartile
131.4
55.66
127.24
5.03
Maximum
1,639.92
776.98
1,634.25
629.54
[2]: Customer minutes of interruption is calculated by multiplying total customers interrupted and total minutes of interruption.
178
Figure 3. Average SAIDI by region
350
Ln
Q1
+ 300
7
C
r- 250
M 200
5
Regions
179
II.2. System Average Interruption Frequency Index
SAIFI is the average instances a customer on the utility system will experience a sustained
fn&numduring a speci
&nrrd MR isre sustained interruption index, only outages lasting longer than
included in the calculations. SAIFI is calculated by dividing the total number of customers that
experienced sustained interruptions by the average number of customers served during that
period. For example, a utility with 150 customer interruptions and 200 customers would have
a SAIFI of 0.75.
Note that in the tables below, scheduled and unscheduled calculations include MEs. Also note
that wherever MEs are excluded, the exclusion is based on the APPA ME threshold for your
system.
T&Wm4e SAIFI with and without MEs
In interruptions
All
No MEs
Unscheduled
Scheduled
Your utility
0.35
0.14
0.35
NULL
Utilities that use the eReliability Tracker
0.78
0.54
0.75
0.06
Utilities in your region
0.52
0.4
0.51
0.03
Utilities in your size class
0.65
0.43
0.63
0.03
%ytefrSary SAIFI data from the eReliability Tracker
In interruptions
i All No MEs I Unscheduled IScheduled
Minimum
<0.01
<0.01
<0.01
<0.01
First Quartile
0.21
0.14
0.19
<0.01
Median
0.54
0.36
0.53
0.01
Third Quartile
1.16
0.77
1.1
0.04
Maximum
3.63
2.43
3.63
2.32
:1
Figure 4. Average SAIFI by region
1.2
Ln
c
0 1.0
Q
0.8
0.6
LL
Q
N 0.4
0)
ra
i
U1 0.2
Q
0.0
5
Regions
181
II.3. Customer Average Interruption Duration Index
CAIDI is the average duration (in minutes) of an interruption experienced by customers during a
fil&de frame.
&nrrejrCL#1RI is a sustained interruption index, only outages lasting longer than
are included in the calculations. CAIDI is calculated by dividing the sum of all customer
minutes of interruption by the number of customers that experienced one or more
#viBrduptjuersadierQngtdmt-perapdr.iThi emetric re
(minutes of duration) during an outage.
Note that in the tables below, scheduled and unscheduled calculations include MEs. Also note
that wherever MEs are excluded, the exclusion is based on the APPA ME threshold for your
system.
ltaWEage CAIDI with and without MEs
In minutes
All
No MEs
Unscheduled
Scheduled
Your utility
118.93
67.46
118.93
NULL
Utilities that use the eReliability Tracker
135.22
92.4
138.62
153.96
Utilities in your region
95.65
83.74
95.41
105.79
Utilities in your size class
1143.62
86.471
143.611
157.41
Tatbtei7ary CAIDI data from the eReliability Tracker
In minutes
All
No MEs
Unscheduled
Scheduled
Minimum
11.21
11.21
10.52
7.82
First Quartile
62.85
51.38
62.41
61.8
Median
93.56
81.55
93.94
95.16
Third Quartile
143.73
110.8
144.19
162.66
Maximum
1,923.68
402.94
2,012.24
1,899.69
182
Figure S. Average CAIDI by region
7200
v
C
E 150
U 100
QJ
cn
(0
? 50
Q
5
Regions
183
II.4. Momentary Average Interruption Frequency Index
MAIFI is the average number of momentary interruptions a utility customer will experience during a
filerie frame.
V�natJi$taksiuith a duration of
MAIFI is calculated by dividing the total number of customers that experienced momentary
interruptions by the total number of customers served by the utility. For example, a utility with
20 momentary customer interruptions and 100 customers would have a MAIFI of 0.20.
ffl&nbeittacy inrndruCiPtieaYvWmbtancffetdmated
outage management system might not log these interruptions; therefore, some utilities have
a MAIFI of zero.
im§.e MAIFI
In interruptions
Your utility
Utilities that use the eReli
Utilities in your region
Utilities in your size class
All
NULL
Tracker 0.45
0.7
0.66
Tabte-Sary MAIFI data from the eReliability Tracker
In interruptions
All
Minimum <0.01
First Quartile <0.01
Median 0.06
Third Quartile 0.53
Maximum 5.0
Figure 6. Average MAIFI by region
0.7
0 0.6
a-�
Q
7
i 0.5
U1
a-�
0.4
LL
0.3
0.2
i
j 0.1
Q
0.0
5
Regions
185
II.5. Average Service Availability Index
ASAI is the percentage of time the sub -transmission and distribution systems are available to serve
fid§#wrfev rcturing a speci
This load -based index represents the percentage availability of electric service to customers
within the period analyzed. It is calculated by dividing the total hours in which 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 period. Note that the higher your ASAI value, the better the performance.
In the tables below, scheduled and unscheduled calculations include MEs. Also note that
wherever MEs are excluded, the exclusion is based on the APPA ME threshold for your system.
Table 10. Average ASAI with and without MEs
In percentage
All
No MEs
Unscheduled
Scheduled
Your utility
99.992
99.9981
99.992
NULL
Utilities that use the eReliability Tracker
99.9775
99.9898
99.9787
99.9976
Utilities in your region
99.9905
99.9939
99.9907
99.9994
Utilities in your size class
99.9817
99.9924
99.9823
99.9991
Table 11. Summary ASAI data from the eReliability Tracker
In percentage
All
I No MEs
Unscheduled
Scheduled
Maximum
99.9999
99.9999
99.9999
99.9999
First Quartile
99.9963
99.9978
99.9964
99.9999
Median
99.9916
99.9949
99.9922
99.9997
Third Quartile
99.9755
99.9894
99.9765
99.999
Minimum
99.6888
99.86
99.6899
99.8856
Figure 7. Average ASAI by region
100.000
Q 99.975
m
C 99.950
UJ
u
N 99.925
a
Q99.900
Ln
Q 99.875
N
En
99.850
v
99.825
99.800
5
Regions
187
II.6. Energy Information Administration Form 861 Data
Form EIA-861 collects annual information on electric power industry participants involved in the
generation, transmission, distribution, and sale of electric energy in the United States and its
territories.
In 2014, Energy Information Administration (EIA) began publishing reliability statistics in Form
EIA-861; therefore, APPA included these statistics in this report for informational purposes.
Please note that the following data includes 174 investor -owned, 467 rural cooperative, and
S2J-hptNodifL0bE4Ar8ft1lities that were large enough to be required to
form. The statistics do not include data from utilities that complete the EIA 861-5 form, which
smaller entities complete. Note that the 327 participating public power utilities include
fid IAJasinunicipal, political subdivision, and state. In addition, since the
collection and release of EIA form data lags by a year, the data is based on 2023 data that was
published October 10, 2024. Therefore, we suggest you only use the aggregate statistics
contained herein as an informational tool for further comparison of reliability statistics.
In Form EIA-861, an entity provides SAIDI and SAIFI including and excluding ME days in
accordance with the IEEE 1366-2003 or IEEE 1366-2012 standard.
Although EIA collected other reliability -related data, the tables below only include SAIDI and
SAIFI data including and excluding ME days. You can download the full set of data at:
www.eia.gov/electricity/data/eia861 /.
Table 12. Your utility's SAIDI and SAIFI with and without IEEE ME days
SAIDI with IEEE ME SAIDI without IEEE SAIFI with IEEE ME days SAIFI without IEEE ME
days (minutes) ME days (minutes) interruptions) days (interruptions)
42.08 9.48 0.35 0.14
Table 13. Summary SAIDI data from Form EIA-861, 2023
In minutes
Average
All
No MEs
376.90
149.41
Minimum
0.20
0
First Quartile
80.88
51.59
Median
178.01
101.18
Third Quartile
392.12
175.32
Maximum
10,820.00
2,475.09
Table 14. Summary SAIFI data from Form EIA-861, 2023
In interruptions
All
No MEs
Average
1.71
1.26
Minimum
0.01
0
First Quartile
0.82
0.60
Median
1.30
0.99
Third Quartile
2.14
1.54
Maximum
17.38
16.92
M0
III. Outage Causes
Equipment failure, extreme weather events, wildlife, and vegetation are some of the most
common causes of electric system outages. The following pie chart shows the percentages of
the primary causes of outages for all utilities using the eReliability Tracker in 2024.
Vdeather -"v
19.3°/a
Equipment
21.2%
VVildlife 16.4%
0.7% Utility Human Error
1.2% Power Supply
4.4%
Public
9.7%
16.2% Unknown
11.0%
Vegetation
r
Scheduled
Figure 8. Primary causes of outages in 2024
Certain factors, such as regional weather and animal/vegetation patterns, can make some
bajnm.Ep 6rAiptiEel-Ehefotlevftisection includes graphs
depicting common causes of outages for your utility, all utilities in your region, and all utilities
using the eReliability Tracker.
@ifwi es: rmtaining aggregate information are customer -weighted to account for di
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. To avoid skewing the data toward large
utilities, the number of cause occurrences is divided by customer size to account for the
€fi-ences. In Figures 9 to 14, the data represent the number of occurrences for each group
190
of 1,000 customers. A customer -weighted occurrence rate of I" means an average of one
outage from that cause occurred per 1,000 customers in 2024.
Note that the sustained outage cause analysis is more comprehensive than the momentary
outage cause analysis due to a larger 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.
191
IIIA. Sustained Outage Causes
In general, sustained outages are the most commonly tracked outage type. In 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
NPor"atrl�norttelbadtagetaghat] Iasnages are classi
b gll lg(e
Figure 9ADpauses of sustained outages for all utilities that use the eReliability Tracker
2.5
0
0
O 2.0
()
d 1.5
a)
V
C
1.0
7
u
u
O 0.5
0.0
Outage Cause Types
€Fe patesMof sustained outages for your utility [31
1.2 -
o 1.0
0
a
i 0.8
(J
a
O 0.2
0.0 -
1.17
0.81
0.22
0.15
Tree Squirrel Vehicle Accident Equipment Wildlife
Outage Cause Types
[3]: The number of occurrences for each cause is divided by the utility's customer count (in thousands) to create an occurrence
ffitwithl#tl4rsiae2ompared across di
192
€ikjoatest4.of sustained outages in your region
20,40
20.0
O 17.5
0
15.0
L
a 12.5
V 10.0
C
N 7.5
7
u 5.0
270
� .
2.5
1.23
0.0
Non -Payment Utility Maintenance and Repairs Squirrel Weather Tree
Outage Cause Types
193
III.2. Momentary Outage Causes
Mkt eb&ptraitWk m me iltaByysbutugdmtan be di
due to the hazard they pose for electronic equipment, it is important to track and analyze the
causes of momentary outages. This section evaluates the common causes of momentary
outages for your utility, region, and size class as well as common causes for all utilities that
faeafthreiI4�bEility Tracker. Please note that only outages lasting less than
#iW0ffiyrMfrUefflMy,,I&bWyures 12
number of occurrences for each cause is divided by that utility's customer count (in
ffrreatarbidtYt6ze3--ate an occurrence rate that can be compared across di
€ Ejpmes*2.of momentary outages for all utilities that use the eReliability
Tracker
0.s
p 0.7
0
0. 0.6
L
U 0.s
u 0.4
C
N
� 0.3
UU
0.2
0
0.1
0.0
Equipment Replacement Other - Vegetation Non -Payment Utility Maintenance and Repairs Unknown
Outage Cause Types
€nes43.of momentary outages for your utility
0.04
O
O
O
rl 0.02
N
PLO
0.oa 0.000 0.000 0.000 0.000 0.000
V
C
N
L
-0.02
U
U
0
—0.04
None None None None None
Outage Cause Types
194
€kjpntisN.of momentary outages in your region
o,
0
0
6
L
W
a5
U
u 4
c
a�
i 3
V
U 2
0
345
0.55 0.54 0.37
Non -Payment Unknown Heat Storm Manufacturing Defect
Outage Cause Types
195
Thank you for your active participation in the eReliability Tracker service. 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
Paul Zummo
Ji Yoon Lee
Matthew Atienza
Gregory Obenchain
Reliability@PublicPower.org
For more information on reliability, visit https://www.publicpower.org/reliability-tracking
Copyright 2025 by the American Public Power Association. All rights reserved.
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