January 12 2018 1
Reliability Metrics and
Reliability Value-Based Planning
Lawrence Berkeley National Laboratory
Distribution Systems and Planning Training
for Midwest Public Utility Commissions January 16-17 2018
Joseph H Eto
January 12 2018 22
Overview of this presentation
Reliability Metrics
Major Events (IEEE Std 1366 definition)
Reliability Value-Based Planning
The Interruption Cost Estimate (ICE) Calculator
Considerations for Reliability Planning Emerging from Recent LBNL
Research
Bibliography
January 12 2018 33
Electricity reliability is measured by the annual average amount of time and frequency that the lights are out
System Average Interruption Duration Index
total duration of sustained customer
interruptions ( 5min each)
------------------------------------------------
number of customers served
SAIDI =
System Average Interruption Frequency Index
frequency of sustained customer
interruptions ( 5min each)
--------------------------------------------
number of customers served
SAIFI =
Customer Average Interruption Duration Index
SAIDI-------------------
SAIFICAIDI =
frequency of momentary customer
interruptions (lt 5min each)
--------------------------------------------
number of customers served
MAIFI =
Momentary Average Interruption Frequency Index
January 12 2018 44
IEEE Standard 1366Investor Owned
Cooperative Municipal
Number of utilities reporting 137 296 117
of US sales by type of utility 51 47 43
SAIDI with Major Events 237 302 115
SAIDI without Major Events 136 159 50
SAIFI with Major Events 14 28 09
SAIFI without Major Events 12 21 07
Information Reported to EIA for 2015
January 12 2018 55
IEEE Standard 1366
First developed in 1998 to define reliability indices amended in 2003 to
add a consistent approach for segmenting Major Event Days (amended
again in 2012 MED definition unchanged)
Uses 25beta to estimate a threshold daily SAIDI Tmed above which a
Major Event Day is identified
◼ Tmed = exp (α+25β)
◼ Beta = log-normal standard deviation
◼ Alpha = log-normal statistical mean
For a normal distribution
◼ Multiplying beta (the standard deviation) by 25 covers 99379 of the
expected observations (assuming a one-sided confidence interval)
◼ For a year of daily observations this translates to an expectation of 23 Major
Event Days per year
But utility daily SAIDI data are not ldquoperfectlyrdquo normally distributed
January 12 2018 66
Daily SAIDI for 5 years (2011-2015)
0000
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
January 12 2018 77
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
200
400
600
800
1000
1200
1400
1600
1800
00 10 20 30 40 50 60 70 80 90 100
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily SAIDI
Frequency
Cumulative
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
50
100
150
200
250
300
350
400
-75
-69
-63
-57
-51
-45
-39
-33
-27
-21
-15
-09
-03
03
09
15
21
27
33
39
45
Mo
re
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily Ln SAIDI
Frequency
Cumulative
Mean = -20Median = -20Std Dev = 13
Mean = 05Median = 01Std Dev = 27
Tmed = e(mean + (25std dev))
Daily SAIDI Re-Ordered from Lowest to Highest
Tmed = 34
January 12 2018 88
0000
1000
2000
3000
4000
5000
6000
7000
U1 Year 2016 Daily SAIDI
4 MEDs in year 20161 Feb 162 Jun 163 Jul 134 Aug 28
TMED = 34
Daily SAIDI for 2016 rarr 4 MEDs
January 12 2018 99
Introducing Reliability Value-Based Planning
The pace of electricity grid modernization efforts will be determined by
decisions made by electric utilities their customers and local
communitiesstates to adopt new technologies and practices
An important motivation for these actions will be maintaining or
improving the reliability and resiliency of electric service
From an economic perspective the justification for these actions will
therefore depend at least in part on
◼ The cost of the actions under consideration
◼ The impact they are expected to have on reliability or resilience and
◼ The value these impacts have to the utility its customers and the
communitystate
Better information will enable but does not guarantee better decisions
and rememberhellip we will never have perfect information
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 22
Overview of this presentation
Reliability Metrics
Major Events (IEEE Std 1366 definition)
Reliability Value-Based Planning
The Interruption Cost Estimate (ICE) Calculator
Considerations for Reliability Planning Emerging from Recent LBNL
Research
Bibliography
January 12 2018 33
Electricity reliability is measured by the annual average amount of time and frequency that the lights are out
System Average Interruption Duration Index
total duration of sustained customer
interruptions ( 5min each)
------------------------------------------------
number of customers served
SAIDI =
System Average Interruption Frequency Index
frequency of sustained customer
interruptions ( 5min each)
--------------------------------------------
number of customers served
SAIFI =
Customer Average Interruption Duration Index
SAIDI-------------------
SAIFICAIDI =
frequency of momentary customer
interruptions (lt 5min each)
--------------------------------------------
number of customers served
MAIFI =
Momentary Average Interruption Frequency Index
January 12 2018 44
IEEE Standard 1366Investor Owned
Cooperative Municipal
Number of utilities reporting 137 296 117
of US sales by type of utility 51 47 43
SAIDI with Major Events 237 302 115
SAIDI without Major Events 136 159 50
SAIFI with Major Events 14 28 09
SAIFI without Major Events 12 21 07
Information Reported to EIA for 2015
January 12 2018 55
IEEE Standard 1366
First developed in 1998 to define reliability indices amended in 2003 to
add a consistent approach for segmenting Major Event Days (amended
again in 2012 MED definition unchanged)
Uses 25beta to estimate a threshold daily SAIDI Tmed above which a
Major Event Day is identified
◼ Tmed = exp (α+25β)
◼ Beta = log-normal standard deviation
◼ Alpha = log-normal statistical mean
For a normal distribution
◼ Multiplying beta (the standard deviation) by 25 covers 99379 of the
expected observations (assuming a one-sided confidence interval)
◼ For a year of daily observations this translates to an expectation of 23 Major
Event Days per year
But utility daily SAIDI data are not ldquoperfectlyrdquo normally distributed
January 12 2018 66
Daily SAIDI for 5 years (2011-2015)
0000
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
January 12 2018 77
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
200
400
600
800
1000
1200
1400
1600
1800
00 10 20 30 40 50 60 70 80 90 100
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily SAIDI
Frequency
Cumulative
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
50
100
150
200
250
300
350
400
-75
-69
-63
-57
-51
-45
-39
-33
-27
-21
-15
-09
-03
03
09
15
21
27
33
39
45
Mo
re
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily Ln SAIDI
Frequency
Cumulative
Mean = -20Median = -20Std Dev = 13
Mean = 05Median = 01Std Dev = 27
Tmed = e(mean + (25std dev))
Daily SAIDI Re-Ordered from Lowest to Highest
Tmed = 34
January 12 2018 88
0000
1000
2000
3000
4000
5000
6000
7000
U1 Year 2016 Daily SAIDI
4 MEDs in year 20161 Feb 162 Jun 163 Jul 134 Aug 28
TMED = 34
Daily SAIDI for 2016 rarr 4 MEDs
January 12 2018 99
Introducing Reliability Value-Based Planning
The pace of electricity grid modernization efforts will be determined by
decisions made by electric utilities their customers and local
communitiesstates to adopt new technologies and practices
An important motivation for these actions will be maintaining or
improving the reliability and resiliency of electric service
From an economic perspective the justification for these actions will
therefore depend at least in part on
◼ The cost of the actions under consideration
◼ The impact they are expected to have on reliability or resilience and
◼ The value these impacts have to the utility its customers and the
communitystate
Better information will enable but does not guarantee better decisions
and rememberhellip we will never have perfect information
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 33
Electricity reliability is measured by the annual average amount of time and frequency that the lights are out
System Average Interruption Duration Index
total duration of sustained customer
interruptions ( 5min each)
------------------------------------------------
number of customers served
SAIDI =
System Average Interruption Frequency Index
frequency of sustained customer
interruptions ( 5min each)
--------------------------------------------
number of customers served
SAIFI =
Customer Average Interruption Duration Index
SAIDI-------------------
SAIFICAIDI =
frequency of momentary customer
interruptions (lt 5min each)
--------------------------------------------
number of customers served
MAIFI =
Momentary Average Interruption Frequency Index
January 12 2018 44
IEEE Standard 1366Investor Owned
Cooperative Municipal
Number of utilities reporting 137 296 117
of US sales by type of utility 51 47 43
SAIDI with Major Events 237 302 115
SAIDI without Major Events 136 159 50
SAIFI with Major Events 14 28 09
SAIFI without Major Events 12 21 07
Information Reported to EIA for 2015
January 12 2018 55
IEEE Standard 1366
First developed in 1998 to define reliability indices amended in 2003 to
add a consistent approach for segmenting Major Event Days (amended
again in 2012 MED definition unchanged)
Uses 25beta to estimate a threshold daily SAIDI Tmed above which a
Major Event Day is identified
◼ Tmed = exp (α+25β)
◼ Beta = log-normal standard deviation
◼ Alpha = log-normal statistical mean
For a normal distribution
◼ Multiplying beta (the standard deviation) by 25 covers 99379 of the
expected observations (assuming a one-sided confidence interval)
◼ For a year of daily observations this translates to an expectation of 23 Major
Event Days per year
But utility daily SAIDI data are not ldquoperfectlyrdquo normally distributed
January 12 2018 66
Daily SAIDI for 5 years (2011-2015)
0000
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
January 12 2018 77
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
200
400
600
800
1000
1200
1400
1600
1800
00 10 20 30 40 50 60 70 80 90 100
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily SAIDI
Frequency
Cumulative
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
50
100
150
200
250
300
350
400
-75
-69
-63
-57
-51
-45
-39
-33
-27
-21
-15
-09
-03
03
09
15
21
27
33
39
45
Mo
re
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily Ln SAIDI
Frequency
Cumulative
Mean = -20Median = -20Std Dev = 13
Mean = 05Median = 01Std Dev = 27
Tmed = e(mean + (25std dev))
Daily SAIDI Re-Ordered from Lowest to Highest
Tmed = 34
January 12 2018 88
0000
1000
2000
3000
4000
5000
6000
7000
U1 Year 2016 Daily SAIDI
4 MEDs in year 20161 Feb 162 Jun 163 Jul 134 Aug 28
TMED = 34
Daily SAIDI for 2016 rarr 4 MEDs
January 12 2018 99
Introducing Reliability Value-Based Planning
The pace of electricity grid modernization efforts will be determined by
decisions made by electric utilities their customers and local
communitiesstates to adopt new technologies and practices
An important motivation for these actions will be maintaining or
improving the reliability and resiliency of electric service
From an economic perspective the justification for these actions will
therefore depend at least in part on
◼ The cost of the actions under consideration
◼ The impact they are expected to have on reliability or resilience and
◼ The value these impacts have to the utility its customers and the
communitystate
Better information will enable but does not guarantee better decisions
and rememberhellip we will never have perfect information
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 44
IEEE Standard 1366Investor Owned
Cooperative Municipal
Number of utilities reporting 137 296 117
of US sales by type of utility 51 47 43
SAIDI with Major Events 237 302 115
SAIDI without Major Events 136 159 50
SAIFI with Major Events 14 28 09
SAIFI without Major Events 12 21 07
Information Reported to EIA for 2015
January 12 2018 55
IEEE Standard 1366
First developed in 1998 to define reliability indices amended in 2003 to
add a consistent approach for segmenting Major Event Days (amended
again in 2012 MED definition unchanged)
Uses 25beta to estimate a threshold daily SAIDI Tmed above which a
Major Event Day is identified
◼ Tmed = exp (α+25β)
◼ Beta = log-normal standard deviation
◼ Alpha = log-normal statistical mean
For a normal distribution
◼ Multiplying beta (the standard deviation) by 25 covers 99379 of the
expected observations (assuming a one-sided confidence interval)
◼ For a year of daily observations this translates to an expectation of 23 Major
Event Days per year
But utility daily SAIDI data are not ldquoperfectlyrdquo normally distributed
January 12 2018 66
Daily SAIDI for 5 years (2011-2015)
0000
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
January 12 2018 77
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
200
400
600
800
1000
1200
1400
1600
1800
00 10 20 30 40 50 60 70 80 90 100
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily SAIDI
Frequency
Cumulative
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
50
100
150
200
250
300
350
400
-75
-69
-63
-57
-51
-45
-39
-33
-27
-21
-15
-09
-03
03
09
15
21
27
33
39
45
Mo
re
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily Ln SAIDI
Frequency
Cumulative
Mean = -20Median = -20Std Dev = 13
Mean = 05Median = 01Std Dev = 27
Tmed = e(mean + (25std dev))
Daily SAIDI Re-Ordered from Lowest to Highest
Tmed = 34
January 12 2018 88
0000
1000
2000
3000
4000
5000
6000
7000
U1 Year 2016 Daily SAIDI
4 MEDs in year 20161 Feb 162 Jun 163 Jul 134 Aug 28
TMED = 34
Daily SAIDI for 2016 rarr 4 MEDs
January 12 2018 99
Introducing Reliability Value-Based Planning
The pace of electricity grid modernization efforts will be determined by
decisions made by electric utilities their customers and local
communitiesstates to adopt new technologies and practices
An important motivation for these actions will be maintaining or
improving the reliability and resiliency of electric service
From an economic perspective the justification for these actions will
therefore depend at least in part on
◼ The cost of the actions under consideration
◼ The impact they are expected to have on reliability or resilience and
◼ The value these impacts have to the utility its customers and the
communitystate
Better information will enable but does not guarantee better decisions
and rememberhellip we will never have perfect information
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 55
IEEE Standard 1366
First developed in 1998 to define reliability indices amended in 2003 to
add a consistent approach for segmenting Major Event Days (amended
again in 2012 MED definition unchanged)
Uses 25beta to estimate a threshold daily SAIDI Tmed above which a
Major Event Day is identified
◼ Tmed = exp (α+25β)
◼ Beta = log-normal standard deviation
◼ Alpha = log-normal statistical mean
For a normal distribution
◼ Multiplying beta (the standard deviation) by 25 covers 99379 of the
expected observations (assuming a one-sided confidence interval)
◼ For a year of daily observations this translates to an expectation of 23 Major
Event Days per year
But utility daily SAIDI data are not ldquoperfectlyrdquo normally distributed
January 12 2018 66
Daily SAIDI for 5 years (2011-2015)
0000
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
January 12 2018 77
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
200
400
600
800
1000
1200
1400
1600
1800
00 10 20 30 40 50 60 70 80 90 100
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily SAIDI
Frequency
Cumulative
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
50
100
150
200
250
300
350
400
-75
-69
-63
-57
-51
-45
-39
-33
-27
-21
-15
-09
-03
03
09
15
21
27
33
39
45
Mo
re
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily Ln SAIDI
Frequency
Cumulative
Mean = -20Median = -20Std Dev = 13
Mean = 05Median = 01Std Dev = 27
Tmed = e(mean + (25std dev))
Daily SAIDI Re-Ordered from Lowest to Highest
Tmed = 34
January 12 2018 88
0000
1000
2000
3000
4000
5000
6000
7000
U1 Year 2016 Daily SAIDI
4 MEDs in year 20161 Feb 162 Jun 163 Jul 134 Aug 28
TMED = 34
Daily SAIDI for 2016 rarr 4 MEDs
January 12 2018 99
Introducing Reliability Value-Based Planning
The pace of electricity grid modernization efforts will be determined by
decisions made by electric utilities their customers and local
communitiesstates to adopt new technologies and practices
An important motivation for these actions will be maintaining or
improving the reliability and resiliency of electric service
From an economic perspective the justification for these actions will
therefore depend at least in part on
◼ The cost of the actions under consideration
◼ The impact they are expected to have on reliability or resilience and
◼ The value these impacts have to the utility its customers and the
communitystate
Better information will enable but does not guarantee better decisions
and rememberhellip we will never have perfect information
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 66
Daily SAIDI for 5 years (2011-2015)
0000
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
January 12 2018 77
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
200
400
600
800
1000
1200
1400
1600
1800
00 10 20 30 40 50 60 70 80 90 100
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily SAIDI
Frequency
Cumulative
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
50
100
150
200
250
300
350
400
-75
-69
-63
-57
-51
-45
-39
-33
-27
-21
-15
-09
-03
03
09
15
21
27
33
39
45
Mo
re
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily Ln SAIDI
Frequency
Cumulative
Mean = -20Median = -20Std Dev = 13
Mean = 05Median = 01Std Dev = 27
Tmed = e(mean + (25std dev))
Daily SAIDI Re-Ordered from Lowest to Highest
Tmed = 34
January 12 2018 88
0000
1000
2000
3000
4000
5000
6000
7000
U1 Year 2016 Daily SAIDI
4 MEDs in year 20161 Feb 162 Jun 163 Jul 134 Aug 28
TMED = 34
Daily SAIDI for 2016 rarr 4 MEDs
January 12 2018 99
Introducing Reliability Value-Based Planning
The pace of electricity grid modernization efforts will be determined by
decisions made by electric utilities their customers and local
communitiesstates to adopt new technologies and practices
An important motivation for these actions will be maintaining or
improving the reliability and resiliency of electric service
From an economic perspective the justification for these actions will
therefore depend at least in part on
◼ The cost of the actions under consideration
◼ The impact they are expected to have on reliability or resilience and
◼ The value these impacts have to the utility its customers and the
communitystate
Better information will enable but does not guarantee better decisions
and rememberhellip we will never have perfect information
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 77
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
200
400
600
800
1000
1200
1400
1600
1800
00 10 20 30 40 50 60 70 80 90 100
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily SAIDI
Frequency
Cumulative
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
50
100
150
200
250
300
350
400
-75
-69
-63
-57
-51
-45
-39
-33
-27
-21
-15
-09
-03
03
09
15
21
27
33
39
45
Mo
re
Fre
qu
en
cy
Bin
Histogram of 2011-2015 Daily Ln SAIDI
Frequency
Cumulative
Mean = -20Median = -20Std Dev = 13
Mean = 05Median = 01Std Dev = 27
Tmed = e(mean + (25std dev))
Daily SAIDI Re-Ordered from Lowest to Highest
Tmed = 34
January 12 2018 88
0000
1000
2000
3000
4000
5000
6000
7000
U1 Year 2016 Daily SAIDI
4 MEDs in year 20161 Feb 162 Jun 163 Jul 134 Aug 28
TMED = 34
Daily SAIDI for 2016 rarr 4 MEDs
January 12 2018 99
Introducing Reliability Value-Based Planning
The pace of electricity grid modernization efforts will be determined by
decisions made by electric utilities their customers and local
communitiesstates to adopt new technologies and practices
An important motivation for these actions will be maintaining or
improving the reliability and resiliency of electric service
From an economic perspective the justification for these actions will
therefore depend at least in part on
◼ The cost of the actions under consideration
◼ The impact they are expected to have on reliability or resilience and
◼ The value these impacts have to the utility its customers and the
communitystate
Better information will enable but does not guarantee better decisions
and rememberhellip we will never have perfect information
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 88
0000
1000
2000
3000
4000
5000
6000
7000
U1 Year 2016 Daily SAIDI
4 MEDs in year 20161 Feb 162 Jun 163 Jul 134 Aug 28
TMED = 34
Daily SAIDI for 2016 rarr 4 MEDs
January 12 2018 99
Introducing Reliability Value-Based Planning
The pace of electricity grid modernization efforts will be determined by
decisions made by electric utilities their customers and local
communitiesstates to adopt new technologies and practices
An important motivation for these actions will be maintaining or
improving the reliability and resiliency of electric service
From an economic perspective the justification for these actions will
therefore depend at least in part on
◼ The cost of the actions under consideration
◼ The impact they are expected to have on reliability or resilience and
◼ The value these impacts have to the utility its customers and the
communitystate
Better information will enable but does not guarantee better decisions
and rememberhellip we will never have perfect information
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 99
Introducing Reliability Value-Based Planning
The pace of electricity grid modernization efforts will be determined by
decisions made by electric utilities their customers and local
communitiesstates to adopt new technologies and practices
An important motivation for these actions will be maintaining or
improving the reliability and resiliency of electric service
From an economic perspective the justification for these actions will
therefore depend at least in part on
◼ The cost of the actions under consideration
◼ The impact they are expected to have on reliability or resilience and
◼ The value these impacts have to the utility its customers and the
communitystate
Better information will enable but does not guarantee better decisions
and rememberhellip we will never have perfect information
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1010
Value-Based Reliability Planning is a means for taking the cost of interruptions borne by customers into utility planning decisions
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1111
Value-Based Reliability Planning example
Distribution Automation
Utility EPB of Chattanooga
Customers Impacted 174000
customers (entire territory)
Investment 1200 automated circuit
switches and sensors on 171 circuits
Reliability Improvement
◼ SAIDI 45 (from 112 to 618
minutesyear)
◼ SAIFI 51 (from 142 to 069
interruptionsyear) (between 2010 and
2015)
$56 M
$268 MBenefits
Investment Costs
Utility Avoided customer outage costs
Annual Costs and Benefits
Avoided Cost of Severe Storm
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1212
ICE Calculator httpicecalculatorcom
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1313
Customer-weighted proportion of SAIDI and
SAIFI due to loss of supply (2008-2014 n = 73)
SAIDI w major events
SAIDI wo major events
SAIFI w major events
SAIFI wo major events
0
2
4
6
8
10
12
2008 2009 2010 2011 2012 2013 2014
Pro
po
rtio
n o
f cu
sto
mer
-wei
ghte
d in
terr
up
tio
ns
d
ue
to lo
ss o
f su
pp
ly
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1414
Still we are moving in the right directionhellip
yet there remains much work to be done
0
5
10
15
20
25
30
lt10 kVn=20
10-19 kVn=189
20-29 kVn=101
30-39 kVn=99
40-65 kVn=6
gt65 kVn=27
Pro
po
rtio
n o
f o
uta
ge d
ue
to L
OS
Maximum distribution voltage
SAIFI mean
SAIFI medianSAIDI mean
SAIDI median
SAIDI and SAIFI due to loss of supply vs maximum reported distribution voltage
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1515
LBNL finds that reliability is getting worse due to
increased severityfrequency of major events
Source Larsen P K LaCommare J Eto J Sweeney Recent Trends in Power System Reliability and Implications for Evaluating Future Investments in Resiliency Energy 117 (2016) 29-46 httpdxdoiorg101016jenergy201610063
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1616
The Costs of Power Interruptions
Interruption Cost
Interruption Duration
Momentary 30 minutes 1 hour 4 hours 8 hours
Medium and Large CampI
Morning $8133 $11035 $14488 $43954 $70190
Afternoon $11756 $15709 $20360 $59188 $93890
Evening $9276 $12844 $17162 $55278 $89145
Small CampI
Morning $346 $492 $673 $2389 $4348
Afternoon $439 $610 $818 $2696 $4768
Evening $199 $299 $431 $1881 $3734
Residential
Morning $37 $44 $52 $99 $136
Afternoon $27 $33 $39 $78 $107
Evening $24 $30 $37 $84 $119
Varies by type of customer and depends on when and for how long their lights are out
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1717
NewEngland
Mid-Atlantic
East NorthCentral
West NorthCentral
SouthAtlantic
West SouthCentral
East SouthCentral
Mountain Pacific
Residential 1 19 2 1 11 1 1 1 3
Commercial 14 23 14 86 19 7 7 4 18
Industrial 14 52 11 12 10 18 18 15 22
0
10
20
30
40
50
60
70
80
90
100
Bac
k-u
p G
ener
atio
n (
BU
G)
shar
e o
f to
tal i
nst
alle
d c
apac
ity
Installed Capacity of Back-up Generation
Source Frost and Sullivan 2015 ldquoAnalysis of the US Power Quality Equipment Marketrdquo Berkeley California Lawrence BerkeleyNational Laboratory LBNL-1003990 August Accessible at httpeetdlblgovsitesallfileslbnl-1003990pdf
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1818
Some themes to keep in mind
ldquoWhats measured improvesrdquo
― Peter F Drucker
ldquoDelegating your accountabilities is abdicationrdquo
― Michael E Gerber
ldquoNot everything that can be counted counts
and not everything that counts can be countedrdquo
― Albert Einstein
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 1919
Bibliography
LaCommare Kristina Hamachi Peter H Larsen and Joseph H Eto Evaluating Proposed Investments in Power System
Reliability and Resilience Preliminary Results from Interviews with Public Utility Commission Staff
2017httpsemplblgovsitesdefaultfileslbnl-_1006971pdf
Larsen Peter H A Method to Estimate the Costs and Benefits of Undergrounding Electricity Transmission and Distribution
lines Energy Economics 60 no November 2016 (2016) 47-61 httpsemplblgovsitesdefaultfileslbnl-1006394_pre-
publicationpdf
Larsen Peter H Kristina Hamachi LaCommare Joseph H Eto and James L Sweeney Assessing Changes in the
Reliability of the US Electric Power System 2015 httpsemplblgovsitesdefaultfileslbnl-188741pdf
Eto Joseph H Kristina Hamachi LaCommare Michael D Sohn and Heidemarie C Caswell Evaluating the Performance
of the IEEE Standard 1366 Method for Identifying Major Event Days View Document IEEE Transactions on Power
Systems 32 no 2 (2016)
Sullivan Michael J Josh A Schellenberg and Marshall Blundell Updated Value of Service Reliability Estimates for
Electric Utility Customers in the United States 2015 httpsemplblgovsitesdefaultfileslbnl-6941epdf
httpsemplblgovresearchelectricity-reliability
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2020
Supporting Slides
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2121
Evaluating the performance of alternatives
to the Standard 1366 method
-100
-80
-60
-40
-20
0
20
40
60
80
100
-400 -300 -200 -100 0 100 200 300 400
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
Effect of changing beta multiplier from 25 to 4
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2222
The effect of using fewer historical years to
calculate Tmed 4 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13
n=8
n=34
n=22
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2323
The effect of using fewer historical years to
calculate Tmed 4 years 3 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17
n=8n=8
n=34n=31
n=22n=21
Ch
ange
in A
vera
ge M
EDs
year
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
January 12 2018 2424
The effect of using fewer historical years to
calculate Tmed 4 years 3 years 2 years
-100
-80
-60
-40
-20
0
20
40
60
80
100
-100 -80 -60 -40 -20 0 20 40 60 80 100
n=13n=17n=8
n=8n=8n=12
n=34n=31n=40
n=22n=21n=17
C
han
ge in
Ave
rage
MED
sye
ar
Change in Standard Deviation of SAIDI wo Major Events
