Modelling Through High Frequency Data Sampling and Other Advantages
by Francis Pelletier - PhD Candidate, ETSChristian Masson – PhD Director, ETSAntoine Tahan – PhD Co-Director, ETS
Martin Jetté, General Manager, OSIsoft Canada ULC
École de Technologie Supérieure
Presented at :
In collaboration with
3
Project’s objectives
1. Improve Actual Power Performance Evaluation Techniques (modelling)
2. Improve Power Performance of Operational Wind Power Plant An energy increase of 1% in energy output could represent a financial benefit of
3-4 Millions Euros (100MW Wind Power Plant)
PhD Project: Power Performance Evaluation and Improvement of Operational Wind Power Plant
/21
4
Advanced Data acquisitioning system
Frequency Sampling = 1 HzNumber of tags per second ≈ 100 000 tagsPI Disk Space per year ≈ 0.6 Tbyte / year/21
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1. High Frequency Data Sampling improves Power Curve modelling
capabilities
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PO
WE
R
TIME
Industry-Standard vs High frequency data sampling(10 minute-average VS 1 second)
Typical industry-standard data logger output (10 minute-average)
1 second data output
Power (10 min)
Power (1 sec)/21
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ACTUALLY AVAILABLE WITH 10 MINUTE-AVERAGE DATA• AVERAGE10min• STD10min• min10min• max10min
NEW METRICS WITH 1 SECOND DATA SAMPLING
• Avg, Std, min, max for period different than 10 minutes • Statistical distribution• Skewness - Kurtosis• Derivatives• Filters / smoothing• Dynamic response• (V10min)2 ≠ (V2)10min
• Etc…
ADVANTAGES RELATED TO HIGH FREQUENCY DATA SAMPLINGNew Metrics
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ADVANTAGES RELATED TO HIGH FREQUENCY DATA SAMPLINGIncreases the Number of Data for Modelling
Period: 2009-02-01 00:00:00
to 2010-02-01 00:00:00 2009-02-01
00:00:00to 2010-02-01 00:00:00
2009-02-01 00:02:00
to 2010-02-01 00:02:00
2009-02-01 00:04:002009-02-01 00:06:002009-02-01 00:08:00
to 2010-02-01 00:04:00 to 2010-02-01 00:06:00 to 2010-02-01 00:08:00 /21
00:00:00 00:10:00 00:20:00 ...
00:05:00 00:15:00
P10min = 100 kW P10min = 500 kW
P10min = 300 kW
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Power Curve Analysis – Standard Analysis
Ref.: Jean-Daniel Langlois – GL : GreenPower Conferences – Houston09
Anemometer
defect
Ice accretion on blades
Tower vibration
Faults and
downtime
High wind speed cut-
out
Pow
er [k
W]
Wind Speed [m/s]/21
10
Problems faced by O&M personel
STD>50kW
Pow
er [k
W]
Wind Speed [m/s]
Power Curve
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Review of literature – Power curve modellingDiscrete models (Bin) P=f(WS@nacelle) IEC61400-12-1
Air density correction TI correction Multivariate analysis
IEC61400-12-2
Parametric models Polynomial functions Logistic function with 4 parameters
(G.A.) Power curve partitions (3 regions)
Stochastic models Markov Chain
Non-parametric models K-NN SVM Boosting Tree ANN etc...
Data Reduction Techniques PCA Self Organizing Map (SOM)
It has been found that the power curve modeling’s precision is difficult to improve because of: - Non-linearities - Interaction between variables
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Some Results with ANN modelingP = f (WS & Air Density)
PO
WE
R [k
W]
Wind Speed [m/s]
Air Density
1.22 kg/m^3
to
1.3 kg/m^3
Some Results with ANN modelingP = f (WS & Turbulence Intensity)
PO
WE
R [k
W]
Wind Speed [m/s]
Turbulence Intensity (TI)
7.5%
to
15%
Some Results with ANN modelingP = f (WS & Wind Shear)
PO
WE
R [k
W]
Wind Speed [m/s]
Wind Shear(V80/V40)
1.15
to
1.5
Some Results with ANN modelingP = f (WS & WSskew)
PO
WE
R [k
W]
Wind Speed [m/s]
Wind Speed Skewness
-0.5
to
+0.25
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2. Other Advantages Related to High Frequency Data Sampling
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Control validation (Cut-in & Cut-out validation)Cut-out
( Low wind speed) Cut-in
168.75
137,5
-18.75
12.5
43.75
75
Cut-in Wind Speed
(3.5 m/s)
Power (1sec)
Wind Speed (1sec)
Enables: - Yaw validation & Yaw error detection - Diverter position - Pitch & RPM validation - Faults investigation - Availability validation - etc... /21
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Enhanced Trouble Shooting PossibilitiesINSTANTANEOUS OVER POWER
Maximum Instantaneous Power
Power (1sec) – Normal BehaviourPower (1sec) – Over Power
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Advantages related to high frequency data sampling III- Trouble shooting possibilities
T X RPMgenerator
PO
WE
R
ENCODER MALFUNCTION (1 second Data)/21
20
• New faults and underperformance investigations techniques• Availability validation • Support for Insurance or legal claims
Ex.: Gear box, blade damage etc…• Advance power curve modelling (Markov chain)• Condition monitoring (ex.: FFT analysis…)• Forecasting Improvement (Ramp)• Improve quality control of data (Outlier’s identification)• Wake’s validation and investigation • Control validation and optimization• Etc…
Other opportunities related to high frequency data sampling
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Conclusion• High frequency data sampling improves modelling
possibilities
• Several other advantages related to high frequency data sampling have been found.
• Future investigations will certainly demonstrate new advantages related to high frequency data sampling of wind power plants
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Merci!
Thank you!
