The Full Picture

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ment of the variability of coastal wind resources can be

readily achieved from space by combining global data

from Scatterometers at O(25km) resolution and

regional data from Synthetic Aperture Radar (SAR) at

O(100m) resolution. Radar data from SAR can also

be used to study the shadow effect of mountains and

the wake created by large turbines, which may reach

more than 20 km downstream of offshore wind farms.

Optimizing design for maintenance operations

Assessing the operability and availability of offshore wind

turbines, including the effects of support logistics and the

numbers and capabilities of maintenance vessels, is a key

part of studying the feasibility of wind farm projects. An

important question arising at the earlier stages of devel-

opment is whether it is more cost effective to spend

money on incremental improvements on turbine relia-

bility, or to buy more maintenance vessels.

EO can help address this question by quantifying the

site-specific met-ocean conditions through long-term

data sets of wind and wave conditions.

Such statistical

information can be used in a variety of applications,

including the determination of the type of vessels

needed for maintenance, the quantification of fatigue

load of an offshore wind turbine, and the optimal design

and assessment of ‘downtime’ for turbines.

Assessing environmental conditions

Wind farms can raise environmental problems such as

the level of noise, visual effect, impact on bird popula-

tions and marine biological activity. In order to assess

the potential environmental impact of planned wind

farms, an acoustic wave and current meter instrument

can be deployed at the site to measure the sediment load.

However, operating in-situ sensors in harsh marine

conditions is challenging and can lead to massive bio-

fouling due to the presence of whelks and eggs covering

the sensor after recovery.

In contrast, monitoring from space suffers from no

such problem and can deliver a synoptic map of sedi-

ment matter. This combines well with the in-situ data

and complements them by providing additional infor-

mation on the spatial distribution of sediments.

The outlook for Earth observation wind data

EO satellites orbiting hundreds of kilometres above the

Earth can help the industry to better harness the power

of wind. EO data provide wind investors and engineers

with wide-area observation that is unavailable any other

way. This data enables them to conduct a first check of

multiple prospective sites (even those inaccessible or

remote) without leaving their office, and at a much

cheaper cost than travelling to the site.

EO is however, only one part of the solution and needs

to be integrated with other ancillary data into wider

knowledge solutions to open new business opportuni-

ties. Realizing the full potential of EO in this context

requires further close collaboration between users and

providers of the technology.

cient and economic operation of the power system when integrating

substantial amounts of wind power.

Satellites can help to improve the accuracy of models by provid-

ing data on weather conditions and boundary conditions, both

onshore (eg orography, surface roughness) and offshore (eg sea

surface temperature), necessary to constrain models. The geospatial

nature of EO data is particularly suited to initialize, validate and force

models as they capture the heterogeneities of factors influencing the

wind flow. For example, satellites can measure the variations in sea

surface temperature, which are responsible for a systematic devia-

tion of the vertical wind speed profile from the standard

Monin-Obukhov theory (typically found for near neutral and stable

conditions).

Synoptic mapping of ocean wind resources

The traditional way to assess the potential energy yield of a prospec-

tive wind farm is by using data from a meteorological mast, which

is very expensive in terms of installation and maintenance. For

example, it can cost around 750, 000EUR for one offshore mast

running for one year. Although this approach is accurate, it can only

provide point-measurement data for a short period of time (typically

one year), while the wind field is generally highly variable in space

and time. Using local data can therefore be an issue to assess effec-

tively the ‘bankability’ of prospective wind farms.

In contrast, satellite measurements of ocean winds provide a

more comprehensive and spatially resolved view of wind clima-

tology data and its associated probability distribution. Satellites

are capable of taking measurements within a few m/s for the wind

speed and approximately 20 deg for the wind direction.

An assess-

Sediment load measured from space and coastal observatories

Map of total suspended matter derived from the optical instrument MERIS on

board ENVISAT for the 29 April 2005. The colour legend displays increasing

sediment concentration going from blue to green to red. The optical instrument

cannot see through clouds, which are represented in white. The location of the

planned Sheringham Shoal offshore wind farm is marked with a cross. The

acoustic wave and current meter sensor used to measure sediment load via

acoustic backscatter intensities is also represented before and after recovery.

In the upper right image the unit is covered by whelks and whelks’ eggs

Source: GRAS, SCIRA Offshore Energy Ltd and Gardline Environmental Ltd

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