Offshore Wind, Power Curves and Wakes

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Offshore Wind, Power Curves and Wakes. J.Tambke, M.Doerenkaemper, G.Steinfeld, L.v.Bremen & Prof. J.-O.Wolff – ForWind & ICBM University of Oldenburg, Germany Prof. T. Osahwa – University of Kobe, Japan Prof. J.A.T. Bye – The University of Melbourne, Australia. Overview. - PowerPoint PPT Presentation

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Offshore Wind,Power Curves and Wakes

J.Tambke, M.Doerenkaemper, G.Steinfeld, L.v.Bremen

& Prof. J.-O.Wolff

– ForWind & ICBM

University of Oldenburg, Germany

Prof. T. Osahwa

– University of Kobe, Japan

Prof. J.A.T. Bye

– The University of Melbourne, Australia

Slide 2

Overview

1. Offshore Performance of Meso-Scale Models

2. Wind Profiles and Thermal Stratification - FiNO1

3. Influence on Power Curves

4. Influence on Wakes

5. Large Scale Wakes

100m height / mean wind speed / 2km domain100m height / mean wind speed / 2km domain

Capacity Factors

Slide 4

FINO1 - 103m heightFINO1 - 103m height

9.73 m/s

9.62 m/s

-0.11 m/s (-1.2 %)

1.48 m/s (15.2 %)

0.94

8,749Sample Number

Regression Line y = 0.968 x + 0.202

Accuracy

OBS Average

WRF Average

Bias

RMSE

Correlation Coeffi.

y = 0.968 x + 0.202

0

5

10

15

20

25

0 5 10 15 20 25

Sim

ula

ted

win

d s

pee

d (

m/s

)

Observed wind speed (m/s)

WRF y = 1.024 x - 0.000

0

5

10

15

20

25

0 5 10 15 20 25

Sim

ula

ted

win

d s

pee

d (

m/s

)

Observed wind speed (m/s)

COSMO

9.73 m/s

9.96 m/s

0.23 m/s (2.4 %)

1.36 m/s (14.0 %)

0.95

8,312Sample Number

Regression Line y = 1.024 x - 0.000

Accuracy

OBS Average

CSM Average

Bias

RMSE

Correlation Coeffi.

Slide 6

Binned Wind-Speed Ratios

FiNO1: Influence of Thermal Stratification

unstable stable

Slide 7

Binned Wind-Speed Ratios

FiNO1: Influence of Thermal Stratification

unstable stable

Slide 8

Speed Ratio u90./u30 vs. 10m/L

WRF

Obs.

Monin-Obukhov

LES: Large Eddy Simulation of Wakes

@ alphaventus

Temporally

averaged u at hub

height

u

+1,7% -3% -0,2%

+2,6% -1,5% -0,2%

6 month values

Influence of Thermal Stability on Power Curves

Slide 10

Influence of Thermal Stability on Power Curves

Slide 11

Influence of Thermal Stability on Wakes

Slide 12

Influence of Thermal Stability on Wakes

Slide 13

Slide 14

Conclusions

2. Power differs by up to 10%

2. Wake effects differ by up to 20%

1. Thermal Stratification has a crucial Impact

on Offshore Wind Profiles and on Wakes

This work was funded by the German BMU within the Project OWEA (RAVE - Research at alpha ventus)

Slide 15

MO-Profiles and Boundary Layer Height zi

Mixing Length Approach from Peña & Gryning [BLM 2008]:

Unstable:

Neutral:

Stable:

Boundary Layer Height:Rossby, Montgomery [1935]

Slide 16

Speed Ratio (u90./u33) vs. Stability (z/L)

unstable

stable

u(90m)

u(33m)

< 1.05

Stability: 40m./L (Sonic.40m)

Slide 17

Speed Ratio (u90./u33) vs. Stability (z/L)

Stability: 40m./L (Sonic.40m)

Peña/Gryning 2008

Slide 18

Meso-scale Models at FiNO1

Mean Wind Speeds at 100m:~10m/s

Mean Potential Power Production:50% of the installed Capacity

Bias

m/s

RMSE

m/s

ECMWF

Op. Analysis

-0.4 1.6

DWD Op. Analysis

<-0.1 1.4

MM5 with NCEP

<-0.1 2.3

(2004)

MM5

with ECMWF

<-0.1 1.5

WRF

with NCEP

<-0.1 1.8

(2006)

FiNO1, alpha ventus

Slide 19

Mean Wind Profiles at FiNO1: DWD, WRF

WRF(MYJ-Scheme)

Observation

DWD-LME

for wind directions between 190° and 250°

Slide 20

Mean Wind Profiles at FiNO1: 0-200m

WRF

Observation

DWD-LME

for wind directions between 190° and 250°

Slide 21

Mean WRF-Profiles and Stability

-0.6

-0.3

0

+0.3

+0.6

10m/Lunstable stable-0.6 < 10m/L < +0.6

Slide 22

Uncertainty in the Wind Shear due to Temperature Errors

1. Two non calibrated Pt100: (δ(T2-T1) = ± 0.12 – 0.16°C)

2. Two calibrated Pt100: (δ(T2-T1) = ± 0.08 – 0.12°C)

3. Temperature difference sensor: (δ(T2-T1) = ± 0.04 – 0.08°C)

U30m= 10 m/s

Class 1

Class 2

Class 3

Bulk and Gradient Methods to calculate Stability are not accurate enough.

Saint-Drenan et al. EWEC 2009

Slide 23

Comparison of Mean Profiles at FiNO1

MO-ICWP

Observation

WAsP

for wind directions between 190° and 250°

Model Input: time series of wind speed at 33m height

WAsP bias = - 0.4 m/sMO-ICWP bias < +0.1 m/s

RMSE(103m) = 11%RMSE(103m) = 5.5%

Slide 24

FiNO1: Comparison of Mean Profiles

MM5(ETA-Scheme o1.5)

Observation

DWD(prog. TKE o2.5)

wind directions between 190° and 250°

Slide 25

DWD-LME Speed Ratios vs. Stability (z/L)

MM5 (NCEP)

ObservationDWD Analysis

wind directions between 190° and 250°

Slide 26

Inertially Coupled Wind Profiles

σu/u vs. Wind Speed (u) at 103m, Jan-Dec 2004

Motivation for Ekman-Approach:Turbulence Intensities at FiNO1 are very low

Slide 27

FiNO1: u* -Velocity and Wind Speed at 40m

u* (Sonic.40m)

Wind Speed (Cup.40m) [m/s]

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