The Good, the Bad and the Ugly Extreme Wind

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The Good, the Bad and the Ugly Extreme Wind

• Wiebke Langreder1
• Jørgen Højstrup1
• Lasse Svenningsen2
• 1 Suzlon Energy A/S, Denmark
• 2 EMD A/S, Denmark

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Contents (Part 3)

• The task Mission Impossible?
• What we have done so far
• What is new
• Our results and recommendations
• Outlook

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Terminology

• Extreme Wind Maximum 10-minute average wind
  speed with recurrence period 50 years
• In IEC language Vref

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Positive Thinking?
Inappropriate
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The task Mission Impossible?

• Predict maximum 10-minute average wind speed in
  50 years.
• Normal situation 1-5 years of data
• Extreme winds are not related to mean wind speed.
  

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The task Mission Impossible?

• Objective
• Choose method to
• Minimize uncertainty
• Minimize bias

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Contents

• The task Mission Impossible?
• What we have done so far
• What is new
• Our results and recommendations
• Outlook

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Establish Method

• Long-time series are split in shorter sub-sets,
• each method is applied to each sub-set.

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True Reference Value

• Assumption
• The true Vref is determined
• using full data set
• extracting Annual Maxima (Periodical Maxima)
• Gumbel distribution

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Method

• Normalisation with this true value

PM LT ? True Vref
N subsets ? N results per method ? Standard
deviation ? Bias
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Previous Methods

• EWTS European Wind Turbine Standard Vref
  depending on k factor
• 360 degree
• sector with highest mean v
• PM Periodical Maximum
• POT Peak-over-threshold

Gumbel
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Contents

• The task Mission Impossible?
• What we have done so far
• What is new
• Our results and recommendations
• Outlook

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New development

• Parameter describing Gumbel distribution are
  determined graphically

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New development

• Possible reasons for non-linearity
• Wrong way to extract extreme events?
• Wrong way to plot/fit?
• No convergence towards Gumbel?

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Better extraction/plotting

• IMIS - Improved method of independent storms
• (Cook/Harris)
• Different two-stage process to extract
• Different way to fit regression

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Improved convergence

• Samples extracted from Weibull parent not
  necessarily exponential
• Slow convergence towards Gumbel (exponential)
• Pre-conditioning
• Substitution of V with Vc
• High end of Vc ? exponential
• Gumbel ? exponential
• Tatata faster convergence

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Pre-conditioning

• Two methods
• V2 (dynamic pressure)
• Vk (Weibull shape parameter (Cook/Harris))

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Additional New Development

• Effect of measurement period
• Length of sub-sets 1, 2, 3 and 5 years

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Contents

• The task Mission Impossible?
• What we have done so far
• What is new
• Our results and recommendations
• Outlook

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Statistical relevance

• 15 sites (Europe, US, Asia, Roaring 40th)
• 158 1 year periods
• 77 2 year periods
• 49 3 year periods
• 22 5 year periods

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Results
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Result - EWTS

• EWTS 360degr lowest results
• EWTS max similar numbers as PM-POT-IMIS
• based on distribution ? less sensitive to actual
  period ?
• very difficult to identify correct sector

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Recommendation (1/3)

• Use POT 2 ( dynamic pressure)
• lowest standard deviation and lowest standard
  error of the mean for 1 year periods
• Disadvantage
• Result very sensitive to highest measured wind
  speed in measurement period

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Recommendation (2/3)

• Use EWTS max (sector with the highest average
  wind speeds)
• Advantage
• Independent of period
• Disadvantage
• Difficult to identify sector

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Recommendation (3/3)

• Combine the two methods
• Engineering approach, taking the average of EWTS
  (max) and POT 2

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Outlook

• Check sensitivity to outlier
• If Vref depends on highest measured wind speed
• Better results for a X year data set by using POT
  for each year seperately and then average?
• Try correlation with NCEP/NCAR to find out about
  level of highest measured wind speed in a sample

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Acknowledgement

• Thanks to
• www.winddata.com
• www.undeerc.org/wind
• www.bom.gov.au/inside/cgbaps