Performance Driven Asset Management at ITC Holdings (ITC)
Janice Yen, ITC HoldingsBrian Slocum, ITC HoldingsLe Xu, Quanta Technology
Don Morrow, Quanta Technology
EEI, Glendale, AZApril 9, 2014
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• Introductions • ITC’s Need• Project Methodology• Evaluation Metrics Utilized• Reliability Analysis• Maintenance & Operational Forecasts• Final Project Recommendations• Critical Success Factors• Q&A
AGENDA
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Who we are:• USA’s 1st Fully Independent
Transmission Company • NYSE: ITC• 15,000 Total Circuit Miles • Customers have a combined
load of 26,000 MWs
• Operating Companies– ITC Michigan – ITCT/METC– ITC Midwest– ITC Great Plains
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ITC HOLDINGS
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ITC SERVICE TERRITORY
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Who we are:• Technical and business
consulting & analysis• Independent arm of
Quanta Services
• Industry thought leaders w/ practical experience – Senior staff with average of 25+
years experience– Talented mid-level and junior staff
poised to become industry leaders
– Balanced organization, including former utility, vendor, NERC senior management
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QUANTA TECHNOLOGY
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• The Top Specialty Contractor serving Utility Industry– NYSE: PWR– S&P 500 company– Ranked #1 utility specialty contractor by
Engineering News-Record – Numerous safety and innovation awards
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PART OF QUANTA SERVICE, CORP.
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PROJECT BACKGROUND
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• Concerns about very old, light duty steel towers in rural portions of the system
• Have experienced a degradation in performance for that asset class
• However, overall system performance had improved so it was necessary to show that any rebuilds were still necessary
• Certain contractual performance targets that needed to be satisfied with distribution company customers
• Project was triggered by light duty tower concerns, but project reviewed all138 kV and 345 kV transmission lines
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ITC PROJECT BACKGROUND
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KK71 LIGHT DUTY STRUCTURE
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• Wanted an asset management assessment that was – Rigorous– Supported the MISO planning process– Utilized available asset information, maintenance records,
inspection findings, and operational history– Would provide a forecast of operational performance so action
could be taken before performance fell below contractual requirements
– Provide an indication of future maintenance activity to facilitate resource planning
– Provide indication of the time frame when maintenance or rebuilds were required
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PROJECT OBJECTIVES
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PROJECT METHODOLOGY
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• Used Quanta Technology’s QT-ROAMSM asset renewal program designed to maintain accepted levels of T&D performance.
• Involved analyzing historical outages, inspection reports and maintenance data/records/guidelines to assess potential degradation of transmission and distribution system reliability.
• Provided a forward, statistical model of asset maintenance activities which is used to forecast future performance.
• Created a forecast sufficient to identify candidates for rebuild, maintenance, or further inspection.
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PROJECT APPROACH
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Define Objectives & Set Up Data
Maintenance Related Analysis
Operations Related Analysis
Correlate Maintenance Forecast to Operations
Largest Risk Since
PDF’dRecords
Translated Analysis into Action Plan
HIGH LEVEL WORK FLOW
Data mining & analysis
What are we trying to achieve?
How do you measure it?
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HIGH LEVEL PROCESS FLOW
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• Ranked circuits by operating performance• Identified main structure types associated with these circuits • Used this main structure type to focus analysis• Gathered additional information from the field as necessary to
support analysis• Computed failure rates for structure and associated equipment• Developed failure rate for entire circuit using all structures• Correlated failure rate with past operational history to forecast
performance• Evaluated rebuild, maintenance or repair options • Developed recommendations
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THE APPROACH
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METRICS
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• Deterministic • Probabilistic• Compliance
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TYPES OF METRICS CONSIDERED
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• N-1 Secured• N-1-1 Secured• N-2 Secured
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DETERMINISTIC METRICS – DID NOT USE
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A variety of metrics can be envisioned for use in evaluating and comparing transmission system performance in the context of applicable NERC standards.
– Total Number of Violations of NERC Standards– Number of Interconnection Reliability Operating Limits (IROLs)
Violations– Number of System Operating Limits (SOLs) Violations– Certified Operators / Total Number of Operators
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NERC COMPLIANCE METRICS – DID NOT USE
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• Element Total Automatic Outage Frequency (TOF)• Element Sustained Outage Frequency (SOF)• Element Momentary Outage Frequency (MOF)• Element Sustained Outage Duration Time (SODT)• Element Sustained Outage Mean Time to Repair (MTTR)• Mean Time Between Sustained Element Outages (Mean “Up Time”)(MTBF)• Median Time to Repair Sustained Element Outage Failure (MdTTR)• Element Availability Percentage (APC)• Percentage of Elements with Zero Automatic Outages (PCZO)• Circuit Total Outage Frequency, Mileage Adjusted (TCOF(100CTmi))• Circuit Sustained Outage Frequency, Mileage Adjusted (SCOF (100CTmi))• Circuit Momentary Outage Frequency, Mileage Adjusted (MCOF (100CTmi))
Notes: Selected TOF, SOF & MOF for the project since they are specified in a METC/Consumer Energy contract which establishes minimum accepted levels of reliability.
SETTLED ON SELECT NERC TADS METRICS
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RELIABILITY ANALYSIS
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• Reliability describes the ability of a system or component to function under stated conditions for a specific period of time.
• Reliability is theoretically defined as the probability of failure.
• Specific techniques are available for particular industries. Some of the more specialized methods are extremely powerful in forecasting the time-to-failure of a product.
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RELIED ON CONCEPTS FROM EMERGINGFIELD OF RELIABILITY ENGINEERING
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• Certain techniques can characterize a wide range of data trends (i.e., increasing, constant, and decreasing failure rates)
• The accuracy of reliability analysis depends on the quality of the data:– Item-specific time-to-failure data for the population being
analyzed.– Data for all items that did not fail.– All experienced failure-mode root causes.
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RELIABILITY ANALYSIS
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• The traditional approach to performing a reliability analysis is to plot the data and the find the best-fit line drawn through the data points.
• The distribution can be two-parameter function
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RELIABILITY ANALYSIS APPLICATION
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MAINTENANCE & OPERATIONALFORECASTS – DATA
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• Operational History • Maintenance History (PDFs)• Asset Registry (Asset Sentry)• Broken down for each type of equipment
– Steel Poles– Wood Poles – Conductors– Foundations– Insulators – Hardware
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DATA REVIEWED
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EQUIPMENT EXAMPLE: 138 KV LATTICE STRUCTURES
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0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Failure Rate
Age
Failure Rate
EXAMPLE - KK71 ANALYSISTOWER MAINTENANCE FORECAST
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EXAMPLE - KK71 ANALYSISCONDUCTOR MAINTENANCE FORECAST
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Failure Rate
Age
Failure Rate
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EXAMPLE - KK71 ANALYSISINSULATOR MAINTENANCE FORECAST
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Failure Rate
Age
Failure Rate
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MAINTENANCE & OPERATIONALFORECASTS - SELECTION CRITERIA
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• 138 kV Circuits– Worst performing 30 circuits were
identified in either the 20 year history or the 8 year history
– 44 total circuits were analyzed in 4 groupings
• KK71 – 10 circuits• KM – 7 circuits• Wood Pole – 19 circuits • Other – 8 circuits
• 345 kV Circuits– Average of 1 or more outages per
year in either the 20 year history or the 8 year history
– 17 Circuits were identified for detailed analysis
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CIRCUIT SELECTION CRITERIA
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• Performed detailed review of 20 year & 8 year operational history by circuit
• Identified failure causes by equipment type
• Compared with overall fleet
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PERFORMED DETAILED REVIEW OFOPERATIONAL HISTORY – KK71 EXAMPLE
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MAINTENANCE FORECASTING
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3.4%
2.7%0.4% 1.5%
1.5%
0.2%0.8%
11.1%
8.0%
1.3%
47.9%
1.5%0.2%
0.2% 0.0% 7.9%
3.3%2.9%
5.2%
Percent Breakdown KK71 Circuits
Anchor
Bent Steel
Breaker
Conductor
Cross Arms
Damper
Foundation
Ground Wire
Guy Wire
Hardware
Insulator
Jumper Sleeve
Lightning Arrestor
PTS
Sign
Sitructure
Tree
Unknown
Blank
MAINTENANCE BREAKDOWN – KK71 CIRCUITS
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0.00
0.10
0.20
0.30
0.40
0.50
0.60
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Failure Rate
Age
Failure Rate
EXAMPLE - KK71 ANALYSISALL COMPONENTS FORECAST
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OPERATIONAL FORECAST
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• Used maintenance & outage history to create correlation
• Used Average Outage history to judge results
Estimated Sustained Outages
Circuit Average Annual Sustained Outages
2004 to 2011
2012 2017 2022 2027 2032
Circuit 1 .5 0.41 0.62 0.92 1.33 1.87Circuit 2 .5 0.03 0.05 0.08 0.13 0.19Circuit 3 .2 0.09 0.15 0.24 0.37 0.54Circuit 4 .2 0.11 0.17 0.27 0.40 0.58Circuit 5 .4 0.44 0.69 1.05 1.54 2.22Circuit 6 0 0.00 0.00 0.00 0.00 0.00Circuit 7 .2 0.04 0.07 0.10 0.15 0.22Circuit 8 1.2 0.17 0.25 0.37 0.55 0.81Circuit 9 .3 0.04 0.06 0.10 0.15 0.21Circuit 10 1.0 0.45 0.72 1.13 1.71 2.51
Circuit
Historical Maintenance
Count
Historical Outage Count Ratio
Circuit 1 14 4 28.6%Circuit 2 86 5 5.8%Circuit 3 6 3 50.0%Circuit 4 12 5 41.7%Circuit 5 8 5 62.5%Circuit 6 16 0 0.0%Circuit 7 101 3 3.0%Circuit 8 32 7 21.9%Circuit 9 15 2 13.3%Circuit 10 12 4 33.3%
CORRELATING MAINTENANCE EXPECTATIONS WITHOPERATIONAL FORECAST
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Notes: 1. Number of forecasted events per year/per circuit.2. Circuits with KK71 structures also include other structure types.3. Highlight shows performance exceeding accepted criteria.
All Structures/All Events All Structures/Sustained Events All Structures/Momentary Events
2012 2017 2022 2027 2032 2012 2017 2022 2027 2032 2012 2017 2022 2027 2032
1.78 2.72 4.02 5.80 8.18 0.41 0.62 0.92 1.33 1.87 1.37 2.09 3.10 4.48 6.31
KK71 CIRCUIT OPERATIONAL FORECAST
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FINAL PROJECT RECOMMENDATIONS
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• Four 138 kV lines to rebuilt between 2015 to 2022– Approval for three lines to rebuilt
and completed by 2015• Three 138 kV lines selected for
tower repair• Four 138 kV lines selected for
wood pole replacement
• Two 138 kV lines needed additional inspections
• Nine 138 kV lines selected for close monitoring
• Six 345 kV lines identified for additional inspections
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FINAL PROJECT RECOMMENDATIONS
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CRITICAL SUCCESS FACTORS
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• Ability to articulate the operational objective.• Ability to translate operational objective into a quantitative metric
(i.e., SAIDI, SAIFI, events/year, etc.)• Asset record, maintenance database & outage history are
available.• Maintenance database & outage history are sufficiently detailed
to allow for correlation of activities
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CRITICAL SUCCESS FACTORS
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• Ability to determine if a maintenance event is triggered by events that are relevant to your business objectives
– Operational– PM Schedules– Inspection Findings
• Maintenance Database needed to be broken down by key equipment types– Poles– Structures– Insulators– Conductors, etc
• The maintenance DB must identify each major piece equipment uniquely (e.g, a specific structure needs to be tracked through the maintenance history).
• Equipment in the maintenance DB needed to be linked to a specific line ID that is universally used throughout the db.
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SUCCESS FACTORS (CONT.)
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• The age of each piece of equipment needed to be available. This is critical for the reliability analysis.
• A period of time was required to clean up the data so that the analysis can be conducted.
• The ability to organize the analysis around a major component of equipment (e.g., specific transmission lines) to forecast operational performance.
• Ideally maintenance database should link equipment to voltage level, but it was not absolutely necessary.
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SUCCESS FACTORS (CONT.)
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Question?
Janice Yen, ITC Holdings, [email protected] Slocum, ITC Holdings, [email protected]
Le Xu, Quanta Technology, [email protected] Morrow, Quanta Technology, [email protected]
