The Good, the Bad and the Ugly Extreme Wind

Wiebke Langreder1

Jørgen Højstrup1

Lasse Svenningsen2

1 Suzlon Energy A/S, Denmark2 EMD A/S, Denmark

Contents (Part 3)

• The task: Mission Impossible?

• What we have done so far

• What is new

• Our results and recommendations

• Outlook

Terminology

• Extreme Wind = Maximum 10-minute average wind speed with recurrence period 50 years

• In IEC language: Vref

Positive Thinking?

Denmark 1999

Spain 2009

Japan

Inappropriate

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.

The task: Mission Impossible?

Objective:

Choose method to – Minimize uncertainty– Minimize bias

Contents

• The task: Mission Impossible?

• What we have done so far

• What is new

• Our results and recommendations

• Outlook

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

LT

Sub-set 1 → Vref

Sub-set 2 → Vref

Sub-set 3 → Vref

Sub-set 4 → Vref

Sub-set 5 → Vref

”True” Reference Value

Assumption

The “true” Vref is determined:

• using full data set

• extracting Annual Maxima (Periodical Maxima)

• Gumbel distribution

MethodNormalisation with this ”true” value

N subsets → N results per method → Standard deviation→ Bias

PM: LT → ”True” Vref

Sub-set 1 → Vref

Sub-set 2 → Vref

Sub-set 3 → Vref

Sub-set 4 → Vref

Sub-set 5 → Vref

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-thresholdGumbel

Contents

• The task: Mission Impossible?

• What we have done so far

• What is new

• Our results and recommendations

• Outlook

New development• Parameter describing Gumbel distribution

are determined graphically

New development

Possible reasons for non-linearity:

• Wrong way to extract extreme events?

• Wrong way to plot/fit?

• No convergence towards Gumbel?

Better extraction/plotting

IMIS - Improved method of independent storms

(Cook/Harris)

Different two-stage process to extract

Different way to fit regression

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

Pre-conditioning

Two methods:

V2 (dynamic pressure)

Vk (Weibull shape parameter (Cook/Harris))

Additional New Development

• Effect of measurement period:

Length of sub-sets: 1, 2, 3 and 5 years

Contents

• The task: Mission Impossible?

• What we have done so far

• What is new

• Our results and recommendations

• Outlook

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

PM PM k PM 2 POT POT k POT 2 IMIS IMIS k IMIS 21 year absolute 97% 91% 90% 98% 92% 91%

std dev 18% 15% 15% 25% 20% 20%

2 year absolute 106% 99% 99% 96% 91% 91% 100% 94% 94%std dev 28% 21% 21% 12% 11% 11% 18% 15% 14%

3 year absolute 108% 101% 101% 95% 91% 90% 100% 95% 95%

std dev 21% 16% 16% 10% 9% 9% 13% 11% 11%

5 year absolute 105% 100% 100% 92% 88% 88% 96% 91% 91%std dev 13% 12% 12% 9% 8% 8% 11% 10% 10%

ResultsPre-conditioning Different Methods

Period

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

EWTS 360

EWTS max

1 year absolute 89% 94%std dev 16% 16%

2 year absolute 87% 95%std dev 14% 16%

3 year absolute 86% 92%std dev 14% 17%

5 year absolute 81% 87%std dev 5% 9%

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

Recommendation (2/3)

• Use EWTS max (sector with the highest average wind speeds)

Advantage:

• Independent of period

Disadvantage:

• Difficult to identify sector

Recommendation (3/3)

Combine the two methods• Engineering approach, taking the average of

EWTS (max) and POT 2POT2

POT 2 EWTS max1 year absolute 90% 93%

std dev 15% 12%

2 year absolute 91% 94%std dev 11% 10%

3 year absolute 90% 91%std dev 9% 11%

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

Acknowledgement

Thanks to

• www.winddata.com

• www.undeerc.org/wind

• www.bom.gov.au/inside/cgbaps