Modelling of Wind Speed Fields over Europe and Power Correlations in a 400 GW Scenario

Jens Tambke, Lueder von Bremen, Michael Schmidt,Gerald Steinfeld, Jörg-Olaf Wolff

ForWind & ICBM / Universität Oldenburg

Frans Van HulleXPwind, Belgium

Overview

Grid Design in the IEE-study „OffshoreGrid“

Mesoscale Wind Power Modelling

Fluctuations and Pan-European Wind Power Correlations

Meshed Prototype Grid

Meso-scale Model: WRF

WRF-speeds [m/s] at 90maverages in 2007

[m/s]

FNL initialization

2-domain-setup, one-way-nesting

1st domain resolution: 27x27 km²

2nd domain resolution: 9x9 km²

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

Mean Potential Power Production:~50% of the installed Capacity

~8760h Bias

m/s

RMSE

m/s

ECMWF

Op. Analysis

-0.4 1.5

DWD Op. Analysis

<-0.1 1.4

MM5 using NCEP

<0.1 2.3

(2004)

MM5

usingECMWF

<0.1 1.5

(2004)

WRF

using NCEP

<-0.1 2.0

(2008)

WRF

usingECMWF

<-0.1 1.5

(2008)

FINO1, alpha ventus

Meso-scale Errors at FINO1

Spatial Smoothing EffectsBelgium / Mid-West EU / EU+No+CH

slide 6

Total European On&Offshore Power

2030: 267 GW inst. Onshore - mean production: 64 GW

127 GW inst. Offshore - mean theoret. prod.: 66 GW[GigaWatt]

Time in the Year [h]

Total Sum

Spatial Smoothing EffectsCorrelation with real German Wind Power Generation

von-Bremen-Map

winter

von-Bremen-MapCorrelation with EU Offshore Wind Power

winter

slide 9

von-Bremen-MapCorrelation with EU Onshore Wind Power

winter

von-Bremen-MapCorrelation with total EU On+Offshore Wind Power

winter

von-Bremen-MapCorrelation with EU Offshore Wind Power

wholeyear

von-Bremen-MapCorrelation with EU Onshore Wind Power

wholeyear

von-Bremen-MapCorrelation with EU total On+Offshore Wind Power

slide 14

Spatial Smoothing Effects1-hour Power Gradients

Monthly Solar & Wind Generation & Load Fluctuations in Europe

consumption anom

aly [GW

] (mean=

357GW

)

PV Wind Lastanomalie

Source:L.von Bremen et al. Proc. 8th Int. Offshore Integration Workshop (Ackermann Workshop), Bremen 2009

„Optimal Mix“ of Solar and Wind for a 100% Supply

Source:L.von Bremen et al. Proc. 8th Int. Offshore Integration Workshop (Ackermann Workshop), Bremen 2009

Conclusions

Meso-scale simulations exhibit stronger variability of regional power than former studies using only global-scale analysis

Large-scale wind power integration (e.g. 80%) will be much easier with an On+Offshore SuperGrid to smooth variability

www.OffshoreGrid.euwww.SafeWind.eu

jens.tambke@forwind.de

Back up slides

Meso-scale Model WRF

WRF model:

NCEP initialization

2-domain-setup, one-way-nesting

1st domain resolution: 27x27 km²

2nd domain resolution: 9x9 km²

Speeds in Storm „Kyrill“, Jan‘07

Hourly WRF-wind speeds [m/s]at 90m height

[m/s]

Storms at FINO1 and in WRF

European On&Offshore Power

Hour of the Year

Power [GW]

June 2030

WRF Wind Speed Profiles & Thermal Stratification

-0.6

-0.3

0

+0.3

+0.6

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

Profiles are bin-averaged between very unstable (convective) situations and very stable stratification: -0.6 < 10m/L < +0.6, where L is the Monin-Obukhov-Length

Mean Wind Profiles at FINO1

WRF

Observation

DWD-LME

for wind directions between 190° and 250°

Slide 26

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

WRF

Obs.

Monin-Obukhov