New patent improves the efficiency of wind turbines applying machine learning algorithms

Navarre, a province in the north of Spain, well known as a wind industry hub, is home to a significant number of developers and manufacturers in the field.

Together Kate Benetis, a British lawyer based in Navarre, and Javier Latasa, a Navarran engineer, have developed and patented a system to improve the efficiency of wind turbines based on real-time correction of wind speed and direction values.

In summary, without this patented system the Wind Turbines cannot face the wind with sufficient precission since it cannot be measured with accuracy, causing a loss of efficiency. The system applies Machine Learning algorithms to improve the efficiency of the wind turbine by instantly correcting the deviation between its ideal and actual orientation. This deviation is caused by an error, provoked by the blade movement, in the measurements of the wind speed and direction (registered at hub height). It also facilitates immediate access to data regarding the true output of the turbines.

Today one of the greatest hurdles facing an operator and owner is the lack of knowledge as to the exact output of the wind turbine in relation to the wind, as it is currently measured by apparatus affected by the movement of the blades. Through this innovative system the information can be automatically corrected by ensuring the wind turbines register the real-time speed and direction of the wind and enabling them to correct their direction and modify the angle of the blades. Thus lengthening their service life and increasing the efficiency at which they work.

Kate and Javier met through the Association of Navarre for Access to Technology (ANATEC.ORG), of which they are both members, and through which they share their passion for renewable energy and new technology.

Contact: +34 675 288 651 / +34 635 040 571

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