Valarie Hines: 2013 Sandia National Laboratoies Wind Plant Reliability Workshop
- 1. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin
Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.
Data Needs for Benchmarking
Your Reliability Performance
Sandia National Laboratories
Continuous Reliability Enhancement for Wind
(CREW) Project
Valerie Hines, Lead Reliability Analyst
Alistair Ogilvie, Project Lead
Cody Bond, Data Team
SAND Report # 2013-6547C
- 2. Sandia National Laboratories
Exceptional Service in the National Interest
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Wind Energy Technologies
Department
FOCUS
Industry needs
Reducing energy cost
Promoting large-scale
deployment of clean,
affordable energy
GOALS
High fidelity modeling
Blade design to eliminate
barriers
Increased energy capture &
improved efficiency
Increased system reliability
Testing at reduced cost
- 3. CREW: Continuous Reliability Enhancement for Wind
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Goal: Create a national reliability database of wind plant operating
data to enable reliability analysis
Protect proprietary information
Enable operations and maintenance
cost reduction
Increase confidence from financial
sector and policy makers
Benchmark reliability performance
Track operating performance at a system-
to-component level
Characterize issues and identify technology
improvement opportunities
Sandia partners with
Strategic Power Systems
(SPS), whose ORAPWind®
software collects real-
time data from wind plant
partners
Key Objectives:
Method:
- 4. Performance Dashboard
Cloud based online analysis – 24x7
RAM and Performance data analysis
One minute statistical data – everyone else uses 10 minute data
ORAP® Transformed data
Fault / Event analysis
Industry benchmarks
IEC / IEEE Availability
reporting
NERC GADS reporting
Data Completeness
and Quality monitoring
metrics
ORAPWind.spsinc.com
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- 5. Presentation Content
Preliminary Results for the 2013 CREW Benchmark
• Results not yet finalized
• October 1: Benchmark published (http://energy.sandia.gov/crewbenchmark)
• Sept. 24-25: Sneak peak at “Optimizing Wind Power O&M”
Illustrations of 3 very different kinds of reliability
benchmark metrics and graphs
• Spell out the data needs for each
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- 6. General Data Types
Raw SCADA
• Key data streams: Operating or fault state, Wind speed, Power
• Recorded very rapidly (on the order of seconds)
Summarized SCADA
• Raw SCADA that has been statistically summarized
– CREW uses mean, standard deviation, minimum, and maximum; and sometimes mode (most
common) for non-numeric values like state
• Recorded at regular intervals (on the order of minutes)
– CREW uses industry-standard 10 minutes
(SCADA) Events
• Summarized downtime records, with a start and end date
• Shows symptom; generally less detail about root cause
Work Orders
• Summarized downtime records, with a start and end date
• Includes more detail about root cause
Analysis Timeframe (Easy to forget!)
• Time period over which data was collected and analyzed
– May be different for different plants or turbines
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- 7. Time Accounting
Data Needs
Raw SCADA
• Select the best ONE state/fault for each moment in time
• Map each state/fault to one time category
– IEC’s Availability standard (61400-26-1) provides a great information model
• Sum time in each category
Analysis Timeframe
• Information Unavailable comes from knowing how much time there was
and subtracting how much time is already accounted
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Event & SCADA Data Source:
- 8. Power Curve
Data Needs
Summarized SCADA
• Create discrete “buckets” for wind speed and power, to allow
grouping
• Count the number of SCADA time periods in each combination
of wind speed bucket and power bucket
• Plot Power bucket vs. Wind Speed bucket, with dot size (or
other 3-D option) proportional to the count of SCADA periods
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Event & SCADA Data Source:
- 9. Event Frequency vs. Downtime
Data Needs
SCADA Events
• Map each state/fault to a wind turbine system (or component)
• Count total number of events for each system; Sum time for each system
Analysis Timeframe
Work Orders
• Combining SCADA with good work orders can reduce “Wind Turbine (Other)”
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Event & SCADA Data Source:
- 10. Observations
Even basic benchmarking requires some deep
up-front thought
• How to organize time (information categories)
• How to organize wind turbine (system breakdown)
• How to map existing data to desired results
CREW Benchmark results are stabilizing
• 2013 Benchmark is looking similar to 2012 Benchmark
Electronics Work Orders are still key
• Biggest reliability impact is still from the “Other” system
• Automated benchmarking for more detailed root cause
relies heavily on electronic work orders
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- 11. Accessing More Information
The 2012 Benchmark presentation and companion technical report are at
http://energy.sandia.gov/crewbenchmark
Sandia keeps an archive of our past wind plant reliability publications at
http://energy.sandia.gov/?page_id=3057#WPR
All wind plant owners, operators and OEM’s are invited to participate.
Please contact:
The data in the CREW database is proprietary to our partners. We are not able to
disclose non-aggregated data.
• Due to a large volume of requests and limited funding, Sandia is not able to provide
customized subsets of aggregated data outside the Department of Energy’s Energy
Efficiency and Renewable Energy program.
• Strategic Power Systems, our corporate partner in this effort, may be able to assist with
more information about wind plant reliability. For more information, please contact SPS’
Jim Thomas.
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Jim Thomas, ORAPWind® Project Manager
Strategic Power Systems, Inc.
Jim.Thomas@spsinc.com
(704) 945-4642
Valerie Hines, Lead Reliability Analyst
Sandia National Laboratories
vahines@sandia.gov
(925) 294-6490