offshore wind farm design: offshore wind climate

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Module 4: Offshore Wind Climate 1/64 OFFSHORE WIND CLIMATE Wim Bierbooms Wind Energy Research Group (Aerospace Eng.)

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Page 1: Offshore Wind Farm Design: offshore wind climate

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OFFSHORE WIND CLIMATE

Wim Bierbooms

Wind Energy Research Group (Aerospace Eng.)

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Overview

Wind climate

• in general• variation in height, space and time• offshore wind measurements• special offshore effects• offshore turbulence / extreme winds

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Overview

Wind climate

• in general• variation in height, space and time• offshore wind measurements• special offshore effects• offshore turbulence / extreme winds

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Introduction

Assessment of wind climate important:

• assessment of resources• determination of gross energy yield• site conditions at installation• accessibility for maintenance• loads on structures

mean wind speed

turbulence extreme wind

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• caused by pressure differences (resulting from temperature differences)

• influenced by earth rotation and terrain

What is wind?

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Overview

Wind climate

• in general

• variation in height, space and time• offshore wind measurements• special offshore effects• offshore turbulence / extreme winds

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G : pressure gradient forceC : Coriolis forceW : drag forceUg: geostrophic windU : wind at the ground

Geostrophic windhighaltitude

lowaltitude

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Coriolis effect

With respect tofixed frame

Fictitious force: just effected by rotating observe r

With respect torotating frame

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Ekman layervariation of wind direction

Surface layervariation of wind speed

Atmospheric boundary layer

~ 1000 m

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Wind profile in surface layer (~100 m)mechanical friction I

Wind profile (wind shear):

href is the reference height (10 m)z0 is the roughness length

=

)/ln(

)/ln()()(

0

0

zh

zhhVhV

refref

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At land• z0 = 0.03- 0.25 mAt sea:• z0 ~ 0.0002 m

but dependent upon • wave height • fetch• wave age

Charnock relation:

; α = 0.0185g

uz

2*

0 α=

Wind profile in surface layer (~100 m)mechanical friction II

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Standard height and roughness:

• 10 min. ( or 1 hour) average

• 10 m. height (= href)

• z0 = 0.03 m

Potential wind speedcorrect for local roughness

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Wind profile in surface layer (~100 m)thermal effects I

Temperature

Hei

ght

• Parcel expands (pressure drops with height) → cools down• Adiabatic: no heat exchange

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Wind profile in surface layer (~100 m)thermal effects II

Temperature

Hei

ght

Unstable atmosphere • Vertical movementsof air due to hotsurface

• Vertical velocity exchange

• Steeper gradient

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Wind profile in surface layer (~100 m)thermal effects III

• stable (cold surface)• neutral• unstable (hot surface)

V

H

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Temperature difference

Average wind - water temperature difference at North Sea location.

• Summer: stabilizing ∆T• Winter: destabilizing ∆T

Month

∆T

Tsea -Tair

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Boundary layer stability at sea

Danish “offshore“ sites

Wind speed

% o

ccur

renc

e

Rødsand (DK)

% o

ccur

renc

e

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Overview

Wind climate

• in general

• variation in height, space and time• offshore wind measurements• special offshore effects• offshore turbulence / extreme winds

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Variability of the wind in time

year month day hour minute second

turbulence, related to

• terrain, obstacles

• storm fronts (gusts)

large scale weather systems

• high/low pressure systems

• seasonal variations time scale

contribution to wind speed

variability

daily patterns (often thermal driven):

• sea breeze

• mountain slope winds

“spectral gap”

Space: 100-1000 km < 1 km < 10 m

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Basic wind statistics

number

V

V

time

pdf

V

time series of

10-min. (1-hour)

means

histogram probability density function

Weibull

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Weibull distribution

probability of wind speed < V:

with k : shape parameter (k ≈ 2 in NW Europe coast)a : scale parameter

)1

1(

)(

k

Va yearavg

+Γ=

k

a

V

e)(

1−

∫∞

−−=Γ0

1)( ββα βα de

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Fit of Weibull distribution – example I

Frequency of occurrence(wind rose)

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Fit of Weibull distribution – example II

Weibull scale parameter Weibull shape parameter

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Overview

Wind climate

• in general

• variation in height, space and time• offshore wind measurements• special offshore effects• offshore turbulence / extreme winds

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Existing offshore wind map

• Evaluation ofoffshore potential

• Extrapolation fromland measurements

• Not suitable forenergy yield calculation

• Coastal effectscause main problems

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How to obtain wind statistics for a given location ?

two basic

options

perform local

measurements

use existing data

not possible to

measure long

enough to obtain

good statistics

data not

representative

problem: solution:

correlate with other

sites which have

reliable long term

statistics

use of correction

methods (fetch,

obstacles on land)

“Measure

Correlate

Predict”

Windatlas

+ correction methods

WAsP

MCP

Other

sources

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WASP offshore (Risø DK)

Determine Offshore wind atlas at 150 m height

• Calculate downward to hub height using local orography

• Account for coastaleffects

• Not yet fully operational

change inroughness

speed-upover hills

sheltermodel

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Available offshore wind dataPlatform data (since ’80)• KNMI, RWS: Measuring Network

North Sea (limited w.r.t. land)• wind and wave data

Other sources• light ships• Voluntary Observing Ships• databases (e.g. NESS / NEXT

“hindcast” data)• pressure data (weather forecast)• remote sensing / satellite data

KNMI wind network (NL)

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Remote sensing

Satelite sampling

• Spatial distribution

• Accuracy 2 m/s

• Time shift

• Satellite passages

• Diurnal cycles !?

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Dutch Offshore wind map

Netherlands' Exclusive Economic Zone

Derived from pressure data (1997-2002)

Height: 120 m

Distribution available for 5 locations

© ECN

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Measure Correlate Predict - example

Background MCP:time series annual wind speedslook similar; high and low valuesoccur at the same years

++

Long term correction factors2 years of measurements of asite near Schiphol+: 0.95x: 1.05

x, +: measurements

xx

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Overview

Wind climate

• in general• variation in height, space and time

• offshore wind measurements• special offshore effects• offshore turbulence / extreme winds

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MCP: dedicated measurements I

Risø/SEAS meteo masts at sea5 locations 50 m height in Danish seas

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MCP: dedicated measurements II

“Fino” platform in German partof the North Sea

105 m height; full site assessment:Hydro, meteo and biological surveys

www.fino-offshore.de

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MCP: dedicated measurements IIIPlatform OWEZ (116 m)• WEOM• 3 levels; 3 sides; booms of 12m• 2003• also metocean data

• “Monitoring- en evaluatieprogramma Near Shore Windpark” by the Dutch Government

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MCP: dedicated measurements IVMeteo masts at sea:• Corrections for mast

shadow• Well proven but

expensive

cup sonic

Sodar / Lidar anemometers• Doppler shift of an acoustic

pulse / laser• Promising but expertise

required

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Hourly variation of offshore wind speed

6.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

hour

10-m

win

d sp

eed

[m/s

]

AUK EUR K13 LEG MPN IJM

‚onshore site‘

**

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Monthly variation of offshore wind speed

5

6

7

8

9

10

11

12

Jan Feb Mrt Apr Mei Jun Jul Aug Sep Okt Nov Dec

10-m

win

d sp

eed

[m/s

]

AUK EUR K13 LEG MPN IJM

Month

∆T

Tsea -Tair

Month

∆T

Tsea -Tair

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Annual variation of offshore wind speed

6.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

10.5

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997

10-m

win

d sp

eed

[m/s

]

AUK EUR K13 LEG MPN IJM

Consequences:

• Annual energyyield / income will vary from year to year !!

• Base energy yield estimation on long period (20-30y)

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55.566.577.588.59

020

4060

80100

120

Offshore versus onshore: wind shear

V (m/s)

H

(m)

• larger V• smaller z 0• stability effects

more important• offshore verification

needed

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Offshore versus onshore: Weibull distribution

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

wind speed at hub height [m/s]

prob

abili

ty [-

]

mean wind speed 6.5 m/s(onshore)

mean wind speed 8 m/s(offshore, Baltic)

mean wind speed 10.1 m/s(remote offshore, North Sea)

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Wind climate offshore versus onshore

onshore offshore

diurnal pattern daily maximum uniform

seasonal pattern less pronounced more pronounced

stability diurnal pattern seasonal pattern

wind profile “unstable” on average “neutral” on average

mean wind speed decreasing inland higher than on land

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Overview

Wind climate

• in general• variation in height, space and time• offshore wind measurements

• special offshore effects• offshore turbulence / extreme winds

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III

up to ~30 km landsea

I

II

“windatlas” methods (zo depends on waves fetch age)

coastal discontinuity zone:

model improvement still underway

Coastal effects I

• strong variations in air/sea temperature gradient

(winter ~ summer onshore ~ offshore wind)

• resulting strong effect upon stability

• further complicated by internal boundary layer effects

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Coastal effects IIchange in surface roughness

External boundary layer External boundary layer

z02

x z01

z

Land Sea

Internal boundary layer(IBL)

5 km

~150 m

land sea

External boundary layer External boundary layer

Internal boundarylayer (IBL)

5 km

~150 m

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Overview

Wind climate

• in general• variation in height, space and time• offshore wind measurements• special offshore effects

• offshore turbulence / extreme winds

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Basic wind statisticsdistinction between long and short term

t →

V →

30 min.

long term

short term

20 m/s

0 m/s

-5 m/s

5 m/s

0 m/s

20 m/s

10 min. 10 min. 10 min.

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RECAP: Basic wind statistics – long term

number

V

V

time

pdf

V

time series of

10-min. (1-hour)

means

histogram probability density function

Weibull

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Basic wind statistics - short term

number

V

V

time (s)

pdf

V

time series of

wind (turbulence)

histogram probability density function

Gauss

0 1 0 2 0 3 0 4 0 5 0 6 0- 5

- 4

- 3

- 2

- 1

0

1

2

3

4

5

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Basic wave statistics - short term

number

η

pdf

η

Gauss

small

waves

narrow

banded

number

H

pdf

H

Rayleigh

Hs

0 1 0 2 0 3 0 4 0 5 0 6 0- 0 . 4

- 0 . 3

- 0 . 2

- 0 . 1

0

0 . 1

0 . 2

0 . 3

0 . 4

Time →

η→ time series of

water elevation

H

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Basic wave statistics - long term

time (days)

time series of

Hs and Tz

(each 3-hour)

scatter diagram (‘2d histogram’)

0 2 4 6 8 1 0 1 2 1 40

1

2

3

4

5

6

Tz → Hs →

Num

ber

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Turbulence - characteristics

• random variations around mean U• turbulence intensity TI= σσσσ/U• production:

– wind shear (mechanical)– buoyant (convective / thermal)

• loss:– dissipation (into heat)

• superposition of eddies, swirls(size from 2 km to 1 mm)

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Intermezzo: spectrum

10-2 10-1 100 10110-4

10-3

10-2

10-1

100

101

102

Frequency →

Spe

ctru

m →

Power spectral density function• ‘distribution of energy content

over frequencies’• area below curve = σσσσ2 (variance)• largest eddies have most energy

(Integral) time scale• measure of time over which wind

speed is correlated

(Integral) length scales• characteristic size of eddy

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Stochastic wind simulation; one-point I

Generation of a 10-min time seriesSummation of harmonics:

Sk: spectrum valueφφφφk: random (uniform 0-2 ππππ)

1

( ) cos( )K

k k kk

u t S f tω φ=

= ∆ +∑ }0 10 20 30 40 50 60

6

7

8

9

10

11

12

Time →

Win

d sp

eed

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Choice of spectrum:• von Karman (isotropic)• KaimalSpectrum depends on:• mean wind speed• length scales• turbulence intensity

(offshore ~ 8%)

Generate wind field for several meanwind speeds• distribution: Weibull

10-2 10-1 100 10110-4

10-3

10-2

10-1

100

101

102

Frequency →

Spe

ctru

m →

0 5 10 15 200

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Mean wind speed →pd

f→0 5 10 15 20

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Mean wind speed →pd

f→

Stochastic wind simulation; one-point II

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Stochastic wind field simulation -example

Wind speed →

Bladed; 3 velocity components:• u; longitudinal• v; lateral• w; vertical

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Onshore vs. offshore turbulence

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Measured offshore turbulence intensity T.I.

10 m30 m50 m

σUT.I. =U

T.I.Windspeed [m/s]

T.I. Height[m]

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Rotational sampling of turbulence

eddies rotor

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0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0- 3

- 2

- 1

0

1

2

3

4

Rotational turbulence spectrum

rotating observer

fixed observer

spectrum

turbulence

V

Time (s)

summation of harmonics(random phases){⇒⇒⇒⇒

⇓⇓⇓⇓

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Extreme winds

• No offshore map (yet)

• Extrapolation of datacovering several years(extreme value theory)

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Extreme value analysis - example

• determine yearly maxima U i

• order them to magnitude:

19.8, 20.7, …. 27.2, 27.5 m/s

• fit to extreme valuedistribution (different functions / methods available)

• read from graph: 50-years value

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Extreme gusts

-2 0 2 4 6 8 10 1215

20

25

30

35

40

Time →

Wind speed →

IEC (included in Bladed):deterministic gustuniform over rotor planealso:

– extreme direction change– combination– extreme wind shear (vertical

and horizontal)

‘Real’• maximum amplitude• maximum rise time

Wind speed →

Wind speed →

Time →

Wind speed →

Time →

Wind speed →

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Wind maximum at relativelow levels (~150 m);larger then geostrophic wind

Stable night time conditions

Common in Baltic Sea;Also in North Sea?

Sodar measurements

Low Level Jet