Latest Issue
 
Windtech International March April 2024 issue

 

FOLLOW US AT

follow

 

follow
Machine Learning Techniques Reduce Uncertainty in Long-Term Performance Reference

ewcEWC Weather Consult, a German pioneer in the optimisation of weather data, has developed a long- term correction method for wind measurements giving far superior results. By using machine learning processes EWC has created a method that successfully minimises yield uncertainties. The new method makes it possible to use non-linear corrections, and by doing so the error in the yield estimates on a wind time-series can be reduced to only 3% on average, even for very complex sites. This is half the error level achieved using the matrix method and one-fifth of the error associated with sector-based linear regression in site assessments.

By Jon Meis, Managing Director, EWC Weather Consult, Germany

Login

 
Use of cookies

Windtech International wants to make your visit to our website as pleasant as possible. That is why we place cookies on your computer that remember your preferences. With anonymous information about your site use you also help us to improve the website. Of course we will ask for your permission first. Click Accept to use all functions of the Windtech International website.