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To support the Dutch Government prepare accurate assessments of the offshore energy production forecasts for the five areas being opened up for tender, the Netherlands Enterprise Agency has called in the support of Ecofys. The sustainability consultancy assisted with testing the accuracy of models and data from collected wind measurements.
Wind farms, both in onshore and offshore forms, have the potential to provide considerable sustainable energy generation. Yet, given the considerable investment in their setup and operations, particularly at sea, developing an accurate assessment of the wind potential remains a key factor in the feasibility studies for decisions about deployment, down the line allowing for more accurate measurements and improvements in decision-making processes.
One of the regions to see considerable investment in wind energy generation is the Netherlands. As part of its overarching energy transition plan, the Dutch Government is aiming to increase its installed wind energy generation capacity to 4,500 MW by 2023, for which it has opened up a tender for the development of new offshore wind farms across five zones.
Sustainability consultancy Ecofys recently announced that its Wind Turbine Testing Service has worked with the Netherlands Enterprise Agency to assess its Light Detection and Ranging devices (LiDAR), and define the certainty with which data, collected from two offshore wind farm zones, can be used in calculation of final wind resource assessments. The LiDAR data is derived from laser based instruments that are able to determine the characteristics of winds blowing up to 200 meters above ground or water level.
“The aim of the study was to quantify the certainty with which the wind data, currently measured at the offshore wind farm zones Hollandse Kust and Borssele, can be used in calculation of final wind resource assessments", explains a spokesperson for the firm.
The calculated uncertainty tables can, according to Ecofys, be used directly in wind resource assessments, as well as provide an oversight of classification uncertainty and site-specific uncertainty components. The uncertainties relate specifically to the devices used for the tests.
