Downscaling and calibration of mesoscale data with Meteodyn WT

to build the wind energy atlas of the Loyalty Islands

Stéphane Sanquer (a), Céline Bezault (b), Didier Delaunay (b) (a) Meteodyn New Caledonia, (b) Meteodyn France

PO.216

1. Weather regimes and orographic circulation around New Caledonia,

J.Fefevre, P. Marchesiello, N. Jourdain, C. Menkes, A. Leroy, Marine Pollution

Bulletin 61 (2010) pp 413-431

2. Boundary Layer Development over a Tropical Island during the Maritime

Continent Thunderstorm Experiment R. Shafer, Journal of atmospheric

science, Vol.58 pp 2163-2179

3. Simulations of nocturnal drainage flows by a q2l turbulence closure model, T.

Yamada, T, Journal of Atmospheric Sciences, vol. 40, Issue 1, pp.91-106

(1983),

4. CORINE land cover technical guide– Addendum 2000, C. Steenmans ,

European Environment Agency, May 2000

New Caledonia is made up of one main island and the

medium size Loyalty islands. The Loyalty Islands are far

enough from the mainland of New Caledonia (almost

100 km) to avoid the electrical net connection. In the

context of getting access to the energy autonomy and

reducing the energy dependence to fuel supply, the

energy department of the Loyalty islands would like to

evaluate the green energy potential, especially the wind

resource of the archipelago.

Wind assessment is needed according to the middle

level of wind speed measured to secure the investment.

The relief is quite flat except the east shore which is

made of cliffs leading to local speed-up of the wind. On

the other hand, the land is covered by forests that could

reduce the wind energy. Two of the islands are wide

enough to induce thermal effects that have to be

considered to catch the breezes and stability effects

combined with the trade winds in the wind simulations.

The main purpose of this paper is to present a wind

energy atlas in this complex area where topographical,

roughness and thermal effects may have the same

order of magnitude. The main parts of the study are :

• Meso-scale simulation to catch the thermal events

such as breezes and nocturnal cooling.

• Micro-scale simulation with Meteodyn WT to include

the topographic and roughness effects in the

downscaling.

• Computation of the wind speed and various statistics

at every point of the islands for the reference period.

The paper presents a method to deliver a wind energy

atlas in an unexplored area far from main lands. The

method was developed by using Mesoscale

simulations, the CFD software Meteodyn WT and day

variability of wind at various meteorological masts. The

paper shows the difficulty for meso scale simulations to

reproduce the nocturnal cooling and its effect on the

wind in this area. Further processing was carried out to

correct the met data and to include speed-up (breeze)

or slow down (nocturnal stability) in the Meteodyn WT

results, this tool delivering only topographical and

roughness corrections.

Abstracts

Methods

Results

Objectives

Conclusions

References

EWEA 2012, Copenhagen, Denmark: Europe’s Premier Wind Energy Event

50 km

Ouvéa

Lifou

Tiga

Maré

The study is devoted to deliver a wind energy atlas for

the Loyalty islands (New Caledonia). The reference

meteorological data are available at three stations. The

paper shows the difficulties of mesoscale simulations to

reproduce entirely the thermal effects (sea breeze,

nocturnal cooling). Further analysis and corrections are

proposed to introduce stability and breeze influence in

the results produced by the CFD software Meteodyn

WT that includes only topographical and roughness

corrections.

Main land

At each time step, the hourly mean velocity was

computed at each grid point at 40 m above the ground

from the meteorological data (10 m above the ground).

These data were corrected by including the mesoscale

thermal effects and the orographic and roughness

influences. Mean quantities such as the mean wind

speed, the energy density, the turbulence intensity, the

Weibull parameters and the yearly production with a

100kW wind turbine were computed on the reference

period.

The east shores of Lifou and Maré are strongly windy

compared to their inland parts. Mean wind speeds reach

7 m/s compared to the 4 m/s of the 10m-met mast mean

velocity. Their shores are complex terrains with cliffs and

steep slopes that induce speed-up of the flow. The land

cover downstream the shore made of forest leads to

slow-down the wind. The mean velocity on the smallest

islands where cooling effects are weak (Tiga and Ouvéa)

reaches 8 m/s at their east shore.

Maps of mean wind speed and energy density (samples)

Simulations were carried out with the following

parameters : Year of computation : 2004, Time step : 3

hours, Size of the domain : 250 km x 200 km, Grid

resolution : 1 km, results : wind speed and direction at

100 m above the ground and temperature gradient.

The diurnal cycle was caught by the model but hourly

velocity amplitude was weaker than the one deduced

from the met data.

With nocturnal cooling, the boundary layer stabilizes

and turbulent exchanges from the trade wind circulation

to the surface circulation vanish (1,2). With the land

heating, pools of cold air disappear and sea breezes

appear until the evening with the next cooling of the

lower layer (2). The nocturnal cooling does not affect

much the circulation at 100 m above the ground. Hence

it would be inadequate to use the present mesoscale

simulations to deduce the wind behaviors at 40 m

above the ground.

The met data of the narrow island (Ouvéa) were used to

extract the synoptic wind velocity and to highlight the

sea breeze and the night cooling contributions on the

diurnal variation of the hourly mean velocity for the

widest island (Lifou and Maré).

The topographic and roughness effects were included

by computing the wind on the 4 islands with Meteodyn

WT (3). Orographic data were loaded from the Georep

© database. Roughness was deduced from Atlas

imagery database converted into roughness length via

the Corine land cover nomenclature (4). Correction

factors were applied to the meteorological data by

including sea breeze and stability contributions deduced

previously (depending on the distance from the east

shore). Cooling effect vanishes close to the shore. For

the widest islands, sea breeze is maximum close to the

shore and vanishes at the center of the island

(convergence zone).

Mean wind speed amplitude

H=100 m above the ground

Mesoscale simulations

Ouvéa

Energy density

H=40m

The mesoscale model used is the weather research and

forecast model (WRF) with the ARW dynamic solver.

WRF solves the compressible Euler equations. Analysis

data from NCEP-FNL available from 1999 were used to

define the global atmospheric behavior without

considering the orographic complexity. Four levels of

mesh refinement (27 km, 9 km, 3 km, 1 km) were

considered (nesting) in order to deliver results on the

final grid by considering the behavior of the large scale

circulation on the area.

Lifou

Umean

H=40m

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

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

DV

(m/s

)

Local Standard Time

Sea breeze-Lifou

Sea Breeze-Maré

Cooling-Ouvéa

Cooling-Lifou

Cooling-Maré

Breeze and cooling effects

H=10 m above the ground

0

1

2

3

4

5

6

7

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

me

an h

ou

rly

win

d s

pe

ed

(m/s

)

Local Standard Time

Ouvéa-MesoLifou-MesoMaré-MesoOuvéa-Met DataLifou-Met DataMaré-Met Data

Mesoscale simulations and met data

H=10 m above the ground