Page 189 - Fundamentals of Ocean Renewable Energy Generating Electricity From The Sea

In Situ and Remote Methods for Resource Characterization Chapter | 7 177

FIG. 7.14 Datawell DWR MK III directional waverider predeployment (left) and postdeployment
(right).

Postprocessing and Interpretation
As discussed in Chapter 4, waves exhibit considerable seasonal and interannual
variability. To reduce uncertainty in resource assessment, it is therefore valuable
to obtain as long a time series as possible from a wave buoy for subsequent
analysis and interpretation. However, obtaining a wave record over, for example,
a decade, is impractical for the majority of wave energy projects, unless
an on-going deployment or historical dataset is available. Therefore, often
shorter duration project-specific wave buoy deployments are used to validate
numerical wave models (Chapter 8), and the outputs of the validated models
(which can be applied to timescales of 10 years or longer, e.g. [17]) can
be used for resource assessment. Under such circumstances, a 1-year wave
buoy deployment would likely suffice, because such a timescale would capture
both seasonal and short-term (e.g. storm) variability. Note that although wave
models applied to relatively long-time periods are useful for quantifying the
resource, only in situ measurements of wave conditions can truly characterize
the resource, because observations include, for example, many nonlinear effects
that are parameterized within wave models (e.g. wave-wave interactions), and
processes that are difficult and computationally expensive to simulate, for
example, interaction between wave and tidal resources.
Postdeployment, the three characteristics of the wave data to be considered,
in relation to wave power, are the temporal, directional, and spectral character-
istics [18].
Temporal characteristics: A wave buoy measures how wave properties such
as significant wave height and wave period evolve over time. A wave time