TGS Expands its Data Coverage for Offshore Wind
By:
Tom Russell
25/08/2021
TGS
TGS, a global provider
of energy data and intelligence, has expanded its coverage of numerical
weather prediction (NWP) model data. The latest model covers a 400,000
square kilometers area off the East Coast US, extending from Massachusetts
to North Carolina. It was selected to inform and enhance wind resource
assessment in the New York Bight Proposed Sale Notice areas.
This wind energy model has been produced in collaboration with Vaisala,
a global leader in weather, environmental, and industrial measurements,
to create a higher resolution dataset than publicly available with coverage
over the key offshore wind industry focus areas in the US coast.
These model results have been validated by publicly available measurements,
including but not limited to Floating Lidar data, to increase confidence
and improve data quality compared to other industry datasets. It will be
further enhanced with proprietary measurements later this year.
Wind developers and other industry stakeholders can compare their assessment
of New York Bight areas with wind conditions over existing leases in their
portfolio using this expansive high-resolution volume. This capability
facilitates a baseline for future validation and post-award analysis.
TGS will now include both US and Scotwind NWP models into a comprehensive
atlas of public and proprietary wind data resources. Combined with TGS
subsidiary 4COffshore’s market intelligence database, this provides a
powerful resource enabling rapid, accurate evaluation of available data
in existing leases, especially for future auctions.
Katja Akentieva, VP New Energy Solutions for Western Hemisphere at TGS,
observes, “We are pleased to provide unique solutions and insights
to the fast-growing offshore wind industry in the US and beyond, enabling
our customers to reduce their commercial risk and improve their understanding
of the energy potential in each lease block. Initial results reveal some
interesting variations, spatial and temporal, which may impact various
components of the wind farm design, construction and energy output.”
