distribution reliability community insights conference august 20-22, 2014 vail, co 1 2014 electric...
TRANSCRIPT
Distribution Reliability
Community Insights Conference
August 20-22, 2014
Vail, CO
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2014 Electric T&D Benchmarking
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Agenda
◼ Overview Industry Perspective (SCQA) 1QC Community Key Success Factors
◼ Performance Profiles & Trends Cost/Service
◼ 2014 Benchmarking Results Functional-specific findings
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Overview
Situation
• Although overall reliability appears to be improving over the last few years, the overall 10 year 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 has become 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.
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Profiles & Trends
2013YE 2012YE
Mean Q1 Q2 Q3# of Bars
Mean Q1 Q2 Q3# of Bars
Network Reliability
SAIFI (inc major events & planned interruptions) 1.20 0.75 1.12 1.58 14 1.51 0.94 1.35 1.92 17
SAIFI (ex major events 2.5 beta method) 0.97 0.73 0.79 1.25 13 1.00 0.69 0.89 1.14 16
CAIDI (inc major events & planned interruptions) 155.62 98.01 124.47 169.95 14 203.47 91.96 126.46 139.52 17
CAIDI (ex major events 2.5 beta method) 111.97 81.00 92.86 110.79 13 94.36 74.04 90.85 106.57 16
SAIDI (inc major events & planned interruptions) 191.34 87.01 141.98 261.26 14 325.14 105.00 157.12 233.50 17
SAIDI (ex major events 2.5 beta method) 108.42 63.50 107.87 123.60 13 94.84 65.81 73.83 115.58 16
Customer minutes interrupted per circuit miles [excluding major events] 4902 3022 4013 4898 14 4433 2941 4176 5056 17
Interruptions per 100 circuit miles [excluding major events] 4430 3383 3916 4717 14 4517 2916 4629 5680 17
Percent of customers with <3 interruptions last year
80.62% 93.20% 77.00% 73.00% 9
Percent of customers with <4 interruptions last year
88.29% 97.70% 88.00% 84.89% 9
Distribution line Reliability Profile
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SAIDI Outcomes
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Including Major Events & Planned Outages Excluding Major Events (2.5 Beta Method)
Including Major Events is mostly better than last year, Excluding Major Events is slightly worse.
Distribution Reliability Pg 4, 5Source: DR5
2013 2014
Mean 95.24 107.82
Quartile 1 66.00 63.63
Quartile 2 73.96 103.94
Quartile 3 111.32 123.56
2013 2014
Mean 325.14 185.25
Quartile 1 105.00 87.76
Quartile 2 157.12 140.45
Quartile 3 233.50 245.66
SAIDI Trend (including major events)
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SAIDI Trend (excluding major events per ieee 1366)
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Profiles: SAIFI Outcomes
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Including Major Events & Planned Outages Excluding Major Events (2.5 Beta Method)
All values are better than last year’s, except first quartile Excluding
Distribution Reliability Pg 8, 10Source: DR5
2013 2014
Mean 1.51 1.18
Quartile 1 0.94 0.76
Quartile 2 1.35 1.10
Quartile 3 1.92 1.47
2013 2014
Mean 1.02 0.97
Quartile 1 0.70 0.73
Quartile 2 0.93 0.82
Quartile 3 1.24 1.23
SAIFI Trend (including major events)
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Saifi trend (excluding major events per ieee 1366)
Profile: CAIDI Outcomes
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Including Major Events & Planned Outages Excluding Major Events (2.5 Beta Method)
Most values are somewhat worse than last year, except mean and 2nd Quartile Including Major Events
Distribution Reliability Pg 12, 14Source: DR5
2013 2014
Mean 203.47 152.38
Quartile 1 91.96 100.50
Quartile 2 126.46 113.85
Quartile 3 139.52 169.90
2013 2014
Mean 93.23 111.62
Quartile 1 74.66 83.47
Quartile 2 89.70 93.43
Quartile 3 103.63 109.84
CAIDI Trend (including major events)
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Caidi trend (excluding major events per ieee 1366)
CAIDI/SAIFI Scatter
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Only 1 of 14 companies is top quartile in all 3
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Benchmarking Results
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Saidi by cause (excluding Major events and planned outages)
Trees and Distribution Equipment make up over 50% of SAIDI for 6 of 15 respondents, over 40% for 12 of 15.
Distribution Reliability Pg 23Source: DR30
Outage Cause per Mile (excluding major events)
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Customer Interruptions per 100 Circuit MilesCustomer Minutes per Mile
2013 2014
Mean 4433 4904
Quartile 1 2941 3158
Quartile 2 4176 4116
Quartile 3 5056 4930
Distribution Reliability Pg 32, 41Source: DR35, DR45, ST35
2013 2014
Mean 4518 4417
Quartile 1 2917 3462
Quartile 2 4630 3935
Quartile 3 5681 4611
Mean is worse, median better than last year for Customer Minutes, mean and median are better for Customer Interruptions
21
Internal SAIDI target (excluding major events)
Mean for Targets is 89 vs. 117 last year.
Distribution Reliability Pg 45Source: DR60
Mean does not include outlier #28
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Percent of customers by number of interruptions
2013 2014
Mean 9.13 11.41
Quartile 1: 3.00 2.23
Quartile 2: 5.00 10.45
Quartile 3: 12.88 15.33
Distribution Reliability Pg 46Source: DR65
Results are not as good as last year
2013 2014
Mean 82.36 81.63
Quartile 1: 92.48 93.85
Quartile 2: 86.50 79.40
Quartile 3: 78.80 75.29
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CEMIn (% of customers with n or more interruptions)
CEMI4CEMI3
2012 2013
Mean 9.13 10.88
Quartile 1: 3.00 2.50
Quartile 2: 5.00 10.45
Quartile 3: 12.88 14.91
2012 2013
Mean 17.15 18.23
Quartile 1: 8.10 7.00
Quartile 2: 14.00 20.60
Quartile 3: 20.43 26.06
Results are not as good as last year
These charts will be in a later edition of the report.Source: DR65
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Percent of customers by interruption duration
Distribution of Outage Durations Percent Customer Interruptions >8 Hours
Distribution Reliability Pg 48Source: DR45, DR80
Mean is better, quartiles worse, this year’s outlier not included in statistics.
2012 2013
Mean 5.11 4.82
Quartile 1: 1.05 2.56
Quartile 2: 3.09 4.48
Quartile 3: 4.66 5.81
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IEEE Major Event Days Per Year
Most companies don’t vary much year to year, but a few have large variations
This chart is not in the current reportSource: DR95
Correlating % SAIDI from major events with major event days yields pretty good results (R 2= .631).
Removing one outlier (64% SAIDI, 2 major event days), yields R2 = .930
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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
Vendor Companies Version Last Upgrade
In-house 31
GE PowerOn 272840
4.0 TSB74.2.14.2.1
11-May13-May13-Dec
Oracle 30* 1.7 2006
ABB 38 4.1 5/27/10
Intergraph 212333
8.31
In Service version 9.2
7/23/1214-Feb
CGI 24 5.5 13-Dec
Other 32 Esri Responder 2013
No Answer 37 1.7.5.2 2007
Distribution Reliability Pg 59-62Source: DR45, DR80
Most commercial products have been upgraded in the last few years. The number of In-house systems has decreased since 2011.
* Company 30 uses a product from SPL, now owned by Oracle
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Improving mapping and connectivity information
Distribution Reliability Pg 62Source: DR127
Action Companies Comment
Regular monitoring 21, 38 21 We create a new map file from GIS on a monthly basis and update dispatchers map files, field users mobile maps get udated quarterly unless a major improvement is made.38 GIS exports each circuit every year.
System Field Survey 31 31 We have recently completed a system phasing check for all lines, devices and meters . We have implented process changes to ensure phasing is captured on all new installs and rehab work.
Exception reporting and correction
33, 23, 37, 40, 24, 27, 32
33 Field corrections, landbase corrections, electrical connectivity tracing23 We produce a weekly connectivity report that shows errors in the system. Designers that work out of the service center are responsible for corrections.37 Observed modeling inaccuracies documented and forwarded for resolution daily. No planned outage request worked unless accurately modeled, with correct connectivity. Procedure in place to pre -model all new major equipment being cut -in on distribution system.
Exception Reporting and Correction is used more than all others combined.
Last Year’s Summary• Regular monitoring – 5• Exception reporting and correction –6• System Update – 1• Other - 1
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Improving mapping and connectivity information (cont.)
Distribution Reliability Pg 62Source: DR127
Action Companies Comment
Exception reporting & correction (Cont’d)
40 Our ADMS reports load flow errors, overloaded xfmrs, overloaded segments, and import errors. These problem areas are a direct result from incorrect customer linking and incorrect connectivity in ourGIS. These errors are corrected in GIS and re-imported into ADMS.24 GIS reviews and updates provided by dispatchers fining conetivity errors27 Automated circuit trace QC routines and reports for data correction32 Fixing modeling errors as they are found.
Other 28 28: Other initiatives have some actions that might improve OMS info
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Percent of outages where ert is provided
Distribution Reliability Pg 65Source: DR135
The vast majority provide ERT’s for all customers
2013 Mean 92%
2014 Mean 87%
ERT Accuracy Definition
31
ERT accuracy is the percent of ERT's that are within X minutes before, and Y minutes after the actual restoration time
4 companies reported using this definition, with X and Y defined below. There is no difference year-to-year for the same companies.
Distribution Reliability Pg 69Source: DR 155
2013 2014
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Reported ERT Accuracy
Not in current reportSource: DR160, DR170
2013 2014
Mean 81% 80 %
Quartile 1 90% 89 %
Quartile 2 85% 85 %
Quartile 3 70% 76 %
There is no standard way to measure ERT accuracy, but all who reported use the X before and Y after definition
Very little difference between this year and last Most are at or near their goal
Goal = 90%
Goal = 90%
Goal = 80%
Goal = 85%
Goal = 68%
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Channels through which customers can get ert
Last YearThis Year
Distribution Reliability Pg 75Source: DR185
Total Respondents 14
Call Center 100%
IVR 78.57%
Internet 78.57%
Mobile App 14.29%
Facebook 7.14%
Twitter 21.43%
Text 7.14%
Other 21.43%
All have multiple channels. All “non-traditional” channels increased, IVR decreased. “Other” reported related to mass communication and communication with Government Emergency Management.
Total Respondents 14
Call Center 100%
IVR 64.29%
Internet 100%
Mobile App 57.14%
Facebook 28.57%
Twitter 42.86%
Text 35.71%
Other 21.43%
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Initiatives taken to improve reliability
2014 2013Total Respondents 14 16Tree Triming 25 29Worst circuit improvement 27 30Outage Process improvement 14 18Sectionalizers 6 5Other (see below)Automation 1 1Reclosers 9 6Inspection & maintenance 0 4
Worst circuit improvement is slightly ahead of Tree Trimming this year. Reclosers was mentioned by multiple companies under “Other”
Distribution Reliability Pg 53, 54Source: DR105, DR106
21 22 23 24 25 27 28 30 31 32 33 37 38 40
Tree Triming 1 1 1 2 3 1 1 3 3 3 3 3
Worst circuit improvement 2 2 3 3 2 3 2 1 2 1 1 2 3
Outage Process improvement 2 2 2 2 3 1 2
Sectionalizers 3 1 1 2 1
Other (see below)
Automation 1
Reclosers 3 3 2 1
Actions to Improve SAIFI/CAIDI
35
Companies have specific approaches to improving each of the standard reliability metrics; several mentioned practice improvements to improve CAIDI
Distribution Reliability Pg 55, 56Source: DR110, DR115
ID Actions to Improve SAIFI Actions to Improve CAIDI
25 Distribution AutomationIncreased focus on first responder staffing; Enhanced underground residential distribution (URD) fault response process
22 Installation of reclosers Increased use of mobile dispatch
31 increasing the number of reclosers & sectionalizersfocused on response times & getting all but the customers directly affected online quickly
28 Recloser program Outage process improvements
33 Tree trimming, sectionalizing, snow brackets Sectionalizing
23 Continued Mainline Maintenance Approach Restoring 'open loops' to normal
37Targeted Reliability Improvement Program (TRIP) on worst performing feeders, installation of additional 13kV and 34kV reclosers
Focus on improving both dispatch and field response times; standardized restoration procedures; installation of sectionalizing disconnect switches for partial restoration
38 Same as for SAIDI Initiatives in DR105 Improve on the dispatch and field restorations processes
40 Animal Guards Take home trucks
24 Poorest performing circuits program, Tree trimming based reliability analysis Poorest performing circuits program, Tree trimming based reliability analysis
21 Tree trimming Tree trimming
30URD replacement, worst performing circuit program, lateral improvement program for poor performing laterals
Recloser sectionalization, outage process improvement, feeder tie switch addition
27 Critical circuit patrols to identify bad/damaged equipmentInstalling Cooper GridSensor's on our lines so we can get a jump on outages and their location.
32 Tree trimming, underground cable replacements No new initiatives
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Analysis
Reliability Correlation with External Factors
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Customer Density (customers/square mile)
The following slides examine the correlation of several features of the system that are not controllable (customer density, circuit density, etc)
Weak correlation, but higher density tends to better reliability
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 Controllable Factors – O&M Spend
40
This slide compares O&M expense per Circuit Mile to SAIDI, SAIFI, CAIDI
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
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Reliability Correlation with Controllable Factors – O&M Spend
This slide compares Average O&M expense per Circuit Mile for the previous 3 years to SAIDI, SAIFI, CAIDI
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.
Reliability Correlation with Controllable Factors – Percent UG
42
This slide compares Percent Underground Distribution to SAIDI, SAIFI, CAIDI
Good correlation with SAIFI, weaker with SAIDI, virtually no correlation with CAIDI
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Reliability Practices and Initiatives of Top Reliability Performers
Legends Total
Tree Triming 1 3 1 3 3 2 13
Worst circuit improvement 1 2 2 2 3 1 11
Outage Process improvement 1 1 3 5
Sectionalizers 3 3
Other (Summarized Below) 2 2 1 2
Reclosers 1 2 3
Repair and Replacement based on Inspection 2 2 4
INITIATIVES TAKEN TO IMPROVE RELIABILITY [RANK THE TOP 3, WITH 3 BEING THE MOST IMPORTANT] -- Top Performers Only
Top 3:1. Tree Trimming2. Worst Circuit Improvement3. Outage Process ImprovementRemainder:• Repair and Replacement based on inspection• Sectionalizers• Reclosers
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Reliability Practices and Initiatives of Top Reliability Performers
Other Characteristics of Top Performers
• None of the top performers relies on an In-house OMS. There is no clear choice among vendors
• Of the 8 top performers, all but two were relatively high density (>400 customer/sq mi), in an arid climate, or both.
• All who reported use some kind of continuous exception and correction routine to maintain mapping and connectivity current
Thank you for your Input and Participation!
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