distribution reliability community insights conference august 19-21, 2015 minneapolis, mn 1 2015...
TRANSCRIPT
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Distribution Reliability
Community Insights Conference
August 19-21, 2015
Minneapolis, MN
2015 Electric T&D Benchmarking
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Agenda
◼ Overview Industry Perspective 1QC Community Key Success Factors
◼ Performance Profiles & Trends Cost/Service
◼ 2014 Benchmarking Results Functional-specific findings Analysis
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Overview
Situation
• Although overall reliability appears to be improving over the last few years, the long-term trend is still decreasing reliability, both as measured by frequency and duration of outages
Complication
• Cost pressures on both O&M and capital make large-scale reliability improvement programs difficult to achieve
•New technologies offer the promise of reduced outages and faster restoration times, but implementation costs are high
Question
• How to improve, or at least maintain reliability at current levels?
• What practices are used by better performers in distribution reliability?
Answer
• Although incremental improvements can be made by process changes, significant improvement for low performers will likely involve significant O&M and/or capital expense
Where Are We: 1QC Industry Perspective for Distribution Reliability
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Summary and conclusions
◼ IEEE 1366 is the predominant standard for measuring reliability.◼ The long-term trend of decreasing reliability appears to be moderating
over the last few years.◼ Initiatives to improve reliability continue to focus on tree trimming,
increased maintenance and process improvement.◼ The majority of utilities are providing Estimated Restoration times for
100% of customer interruptions◼ Top performers tend to have characteristics that are endemic to their
system (climate, population density, etc).
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Profiles & Trends
Distribution Reliability Profile
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2014YE 2013YE Mean Q1 Q2 Q3 Bars Mean Q1 Q2 Q3 BarsReliability
SAIFI (inc major events & planned interruptions) 1.17 0.78 1.13 1.48 16 1.18 0.76 1.10 1.47 15
SAIFI (ex major events 2.5 beta method) 0.93 0.75 0.86 1.14 15 0.97 0.73 0.82 1.23 15
CAIDI (inc major events & planned interruptions) 151.62 91.72 111.45 149.70 16 152.38 100.50 113.85 169.90 15
CAIDI (ex major events 2.5 beta method) 89.94 77.97 85.10 100.84 15 111.62 83.47 93.43 109.84 15
SAIDI (inc major events & planned interruptions) 192.96 80.46 144.67 208.43 17 206.55 88.52 141.98 285.49 16
SAIDI (ex major events 2.5 beta method) 90.35 57.22 80.00 111.05 16 111.63 63.75 107.87 131.26 16
Customer minutes interrupted per circuit miles [excluding major events]
4176 2576 3729 4553 12 5108 3026 4441 4932 12
Interruptions per 100 circuit miles [excluding major events]
4660 3324 3722 6113 13 4642 3621 4072 4713 13
Percent of customers with <3 interruptions last year 89.80% 93.48% 89.40% 88.03% 11 87.63% 93.65% 90.70% 81.85% 11
Percent of customers with <4 interruptions last year 95.08% 97.35% 95.40% 94.28% 11 93.87% 97.93% 95.95% 90.28% 11
Most measures are marginally improved over the previous survey
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Profiles: SAIDI Outcomes
Including Major Events Little Changed From Last YearExcluding Major Events Significantly Improved
Including Major EventsDistribution Reliability, Page 4, Question DR5
Excluding Major Events (2.5 Beta)Distribution Reliability, Page 6, Question DR5
2014 2015
Mean 185.25 192.96
Quartile 1 87.76 80.46
Quartile 2 140.45 144.67
Quartile 3 245.66 208.43
2014 2015
Mean 107.82 90.35
Quartile 1 63.63 57.22
Quartile 2 103.94 80.00
Quartile 3 123.56 111.05
SAIDI Trends
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Including Major Events Varies with WeatherExcluding Major Events improving since 2010, except for the bottom quartile.
Distribution Reliability, Question DR5
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2014 2015
Mean 1.18 1.17
Quartile 1 0.76 0.78
Quartile 2 1.10 1.13
Quartile 3 1.47 1.47
Profiles: SAIFI Outcomes
Including Major Events is essentially unchanged over last yearExcluding Major Events shows slightly improved mean, due to significant improvement in 3rd Quartile
Including Major EventsDistribution Reliability, Page 8, Question DR5
Excluding Major Events (2.5 Beta)Distribution Reliability, Page 10, Question DR5
2014 2015
Mean 0.97 0.93
Q1 0.73 0.75
Q 2 0.82 0.86
Q 3 1.23 1.14
SAIFI Trends
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Including Major Events varies with weatherSince 2010, all measures are improving
Distribution Reliability, Question DR5
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Profile: CAIDI Outcomes
Including Major Events is slightly improved over last yearExcluding Major Events is significantly better
Including Major EventsDistribution Reliability, Page 12, Question DR5
Excluding Major Events (2.5 Beta)Distribution Reliability, Page 14, Question DR5
2014 2015
Mean 152.38 151.62
Quartile 1 100.50 91.72
Quartile 2 113.85 111.45
Quartile 3 169.90 149.70
2014 2015
Mean 111.62 89.94
Quartile 1 83.47 77.97
Quartile 2 93.43 85.10
Quartile 3 109.84 100.84
CAIDI Trends
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CAIDI Including varies with weather. However, the first quartile changes little. Excluding is improving slowly since 2010.
Distribution Reliability, Question Used DR5
CAIDI/SAIFI Scatter
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3 of 16 companies are top quartile in all 3
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Benchmarking Results
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Outage Cause per Mile (excluding major events)
Customer Minutes is Lower this year.Customer Interruptions is Higher.
Customer Minutes per MileDistribution Reliability, Question DR35, ST35
Customer Interruptions per 100 Circuit MilesDistribution Reliability, Question DR45, ST35
2014 2015
Mean 4904 4176
Quartile 1 3158 2576
Quartile 2 4116 3729
Quartile 3 4930 4553
2014 2015
Mean 4417 4660
Quartile 1 3462 3324
Quartile 2 3935 3722
Quartile 3 4611 6113
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Internal SAIDI target (excluding major events)
• Average SAIDI is 105% of Target
• 8 of 13 were above target• 5 of 13 were below target • 2 were within 1%• Mean target is 87 minutes
this year vs 89 minutes last year
Companies appear to be setting reasonable targets
Distribution Reliability Report page 51Question DR60
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Customers Experiencing Multiple Interruptions
Results are Much Better than Last Year
Percent of Customers with <3 InterruptionsDistribution Reliability Question DR55, page 52
CEMI3 (Customers with >=3 Interruptions)Distribution Reliability Question DR55, page 53
2014 2015
Mean 81.63 89.80
Quartile 1 93.85 93.48
Quartile 2 79.40 89.40
Quartile 3 75.29 88.03
2014 2015
Mean 18.23 10.20
Quartile 1: 7.00 6.52
Quartile 2: 20.60 10.60
Quartile 3: 26.06 11.97
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Percent Of Customers By Interruption Duration
Results not as good as last yearStatistics do not include outliers
Size of each graph = 4” x 4”
Location (from top left corner) = H 0.59” & V 2.61”
Size of each graph = 4” x 4”
Location (from top left corner) = H 5.33” & V 2.61”
Percent Customer Interruptions by DurationDistribution Reliability Questions DR80, DR45, p
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CELID8 (% Customer Interruptions >8 Hours)Distribution Reliability Questions DR80, DR45, p
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2014 2015
Mean 4.82 5.98
Quartile 1 2.56 2.87
Quartile 2 4.48 6.46
Quartile 3 5.81 8.56
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IEEE Major Event Days Per Year
This chart is not in the current reportSource: DR95
Correlating % SAIDI from major events with major event days yields pretty good results Last Year, R2 = .631
Similar Results This Year, R2 = .578
Most have relatively consistent numbers, a few not.
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Initiatives
◼ Outage Management Systems OMS information Improving mapping and connectivity information Strategies to improve effectiveness of OMS
◼ Estimated restoration times (ERT’s) Where provided ERT accuracy
◼ Worst circuit performance
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OMS Vendor, version, and date of last major upgrade
For the first time, there are no In-house Outage Management Systems. All but one have been updated in the last 18 months
Vendor Companies Version Last Update
In house
GE PowerOn 32 No Response No Response
Oracle 3740
1.111.7.5.2
10/15/142007
ABB243338
No Response7.2.27.2
No Response1/23/154/15/15
Intergraph 2227
No Response8.3
Feb-148/13/14
CGI 2325
5.55.02.00
Dec-135/8/14
Other (Schneider Electric ADMS) 21 3.4.2 No Response
No Vendor listed 3031
5.5.004.3
8/15/146/1/14
Distribution Reliability pp 69,70,71Question DR125
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Improving Mapping And Connectivity Information
As OMS/GIS systems become more integrated, exception correction and reporting has become predominant
Action Companies Comment
Regular monitoring 33 33-GIS exports each circuit every year.
Exception Correction and Reporting 38,21,30,23,37,31
38-As issues with the network connectivity are found, distribution controllers and or operations support teams make temporary updates to OMS and then communicate them to GIS so permanent fixes can be made. Distribution Data Exception (DDE) project is working to improve the phasing connectivity data.21-Using ADMS to clean up GIS data. ADMS violations report lists overloaded devices to identify mislinked transformer/customers or other errors. Field check to verify.30-Mapping and connectivity changes are identified by end users. A change request is created; GIS reviews and updates.23-GIS reviews and updates provided by dispatchers finding connectivity errors.37-Constant partnership with mapping resources in the field. If found wrong today, it is fixed in OMS tomorrow31- Daily QC routines for customer and facility connectivity
Other 40,27,25
40-Procedure in place to pre-model all new major equipment prior to cut-in27-Working to improve migration process25-Field Verification
Last Year’s Summary• Regular monitoring – 2• Exception reporting and correction –7• System Field Survey – 1• Other - 1
Distribution Reliability pp 73Question DR127
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Percent Of Outages Where ERT Is Provided
• Mean History• 2013 – 92%• 2014 – 87%• 2015 – 99%
Unless something changes, we won’t show this chart again
Mean is 99%All but 1 100%
Distribution Reliability Page 75; Question Used: DR135
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Goal = 70% (120 min before, 60 min after)
Goal = 100% (No Definition Provided)
Goal = 90% (60 min before, 15 min after)
ERT Accuracy, Goals, and Definition, Process
• ERT accuracy seems to be less of a concern
• Most provide ERT either at the initial call or soon after
• A few provide after dispatch• Some with mobile data
update after evaluation
Only 3 provided measured accuracy, although 5 provided definitions.
Distribution Reliability pp 76-87, Questions DR 135-180
Reported Accuracy of ERT’s
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Channels Through Which Customers Can Get ERT
This YearLast Year
Distribution Reliability Pg 88-89Source: DR185
Total Respondents
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Call Center 100%
IVR 64.29%
Internet 100%
Mobile App 57.14%
Facebook 28.57%
Twitter 42.86%
Text 35.71%
Other 21.43%
Total Respondents 13
Call Center 100%
IVR 69.23%
Internet 92.31%
Mobile App 76.92%
Facebook 23.08%
Twitter 46.15%
Text 38.46%
Other 38.46%
Legends 21 22 23 24 25 27 30 31 32 33 37 38 40
Call Center ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦IVR ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦Internet ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦Mobile App ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦Facebook ♦ ♦ ♦Twitter ♦ ♦ ♦ ♦ ♦ ♦Text ♦ ♦ ♦ ♦ ♦Other ♦ ♦ ♦ ♦ ♦
All have multiple channels. Most “non-traditional” channels are relatively stable. Other mostly refers to mass communication for widespread outages
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For Planned Outages, When Do You Notify Customers And What Do You Tell Them
Lead times for advance notice vary widely, and according to the situation. There is no consensus.
Companies Advance Notice Notification Information
24,38,25 >1 week
24-2 weeks in advance by letter, reliability improvement work, may be cancelled due to system conditions38-When there is a 10 day lead time for the outage, a letter is sent to the customer informing them of the planned outage. When the planned outage date is less than 10 days, the CR is notified of te planned outage.25-We start notifying customers 11 days prior to the outage. Customers are told that start/end times are not exact.
33,30,31 <1 week
33-48 hrs in advance. Electric Service will be temporarily interrupted as crew members are making equipment repairs and reliability improvements during this time30-For planned outages, customers are notified 24 hours prior to the outage. The customer is told the expected start time and the projected end time for the outage. They are also told why the outage is required31-Normally 1-3 days prior with start/stop times the customer can expect
40,21,23,27,37 Other
40-Usually notify customers well in advance so that their needs can be considered. Provide on-line information for customers to check the status of planned outages.21-Red door hangers are used prior to the planned outage…An electric crew will need to do maintenance work; your electric service will need to be out for approximately _____hrs/min on <date> from <time> to <time>. If you have questions please call <number>23-Customers are notified as early as possible, town hall meetings, or with the customer.27-Certain customers and situations get 24 hour notification37-Residential outages under 4 hours are given limited notice, >4 hours are notified. Commercial customers are scheduled in advance according to their schedule.
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Most Important Initiatives Taken To Improve Reliability
2015 2014 2013Total Respondents 14 14 16Tree Triming 24 25 29Worst circuit improvement 28 27 30Outage Process improvement
13 14 18
Sectionalizers 16 6 5Other (see below) 1Automation 1 1Reclosers 2 9 6Inspection & maintenance 0 4
Distribution Reliability Pg 65, 66Source: DR105, DR106
Legends 21 22 23 24 25 27 28 30 31 32 33 37 38 40Tree Triming 3 1 2 3 1 3 3 1 1 3 3Worst circuit improvement
2 3 3 2 3 2 1 3 2 3 1 1 2
Outage Process improvement
2 1 2 2 1 2 3
Sectionalizers 1 1 2 3 2 1 3 2 1Other 1 2
Worst circuit improvement is again slightly ahead of Tree Trimming this year. Sectionalizers moved ahead of Outage Process Improvement
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Blue Sky Trouble Call Response
There is a large variation in response times. Time to dispatch varies from 12 minutes to 180 minutes; Crew travel time from 31 to 100. On-site repair times are pretty consistent
Average Time From First Customer Contact To When Lights Are Turned On
Distribution Reliability Page 96, Question DR225Distribution Reliability Page 95, Question DR225
Blue Sky Trouble Call Resonse –Average Time Intervals
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Analysis
Reliability Correlation with External Factors
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Customer Density (customers/square mile)
Weak correlation, but higher density tends to better reliability
The following slides examine the correlation of several features of the system that are not controllable (customer density, circuit density, etc)
Reliability Correlation with External Factors – Cust per Ckt Mile
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Customer Density (customers/square mile)
Weak correlation, but higher customers per ckt mile tends to lower CAIDI
Reliability Correlation with Controllable Factors – Work Headquarters
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Weak Correlation for both, but higher sq miles per work center tends to have higher CAIDI.
The following slides examine the correlation of several features of the system that are controllable (work headquarters, O&M spend, SCADA penetration, etc)
Reliability Correlation with External Factors – Current Year Reliability
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Fair correlation, as expected, higher SAIDI, SAIFI, CAIDI leads to more restoration expense
Reliability Correlation with Controllable Factors – Percent UG
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Good correlation with SAIFI, weaker with SAIDI, virtually no correlation with CAIDI
This slide compares Percent Underground Distribution to SAIDI, SAIFI, CAIDI
Reliability Correlation with Controllable Factors – O&M Spend
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Correlations are very weak, and tend to show increased frequency and duration for increased spending. This is probably due to the fact that the spending is in response to poor reliability in past years
This slide compares current year O&M expense per Circuit Mile to SAIDI, SAIFI, CAIDI
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Reliability Correlation with Controllable Factors – O&M Spend
Correlations are much better comparing O&M spend for recent years to current years reliability. This makes sense since money spent in the current year would only have minimal effect on this year’s reliability.
This slide compares Average O&M expense per Circuit Mile for the previous 3 years to SAIDI, SAIFI, CAIDI
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Reliability Correlation with Controllable Factors – Capital Spend
Correlations are also good comparing “Maintenance” capital (Repair/Replace in kind) to reliability measures
This slide compares Average “Maintenance” Capital Spend per Circuit Mile for the previous 3 years to SAIDI, SAIFI, CAIDI
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Reliability Correlation with Controllable Factors – Capital Spend
Correlations are somewhat better using the sum of O&M and Capital spends
This slide compares the sum of Average “Maintenance” Capital Spend per Circuit Mile and O&M less Service Restoration for the previous 3 years to SAIDI, SAIFI, CAIDI
Thank you for your Input and Participation!
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