Improved icing prediction for wind farms thanks to comprehensive data analysis
Wind farm operators especially in the USA and Scandinavia will be pleased. The icing prediction from energy & meteo systems profits from even more precise predictions by the new partner project PiB, "Predictive, intelligent operational control for reducing the risk of icing for wind energy turbines." Since the start of 2018, the prediction service provider from Oldenburg has worked together with partners from the University of Bremen, wpd windmanager and Spitzner Engineers on an intelligent prediction technology to recognize the risk of icing as well as in the research of methods to reduce this risk, as the icing of wind turbines can lead to enormous power losses and associated losses of yield as well as to complete operational failures. The three-year project is sponsored by the Federal Ministry for Economic Affairs and Energy.
Identify icing risk early
In the development of the smart prediction system towards the reduction of the risk of icing from wind energy turbines, a novel, comprehensive approach on the basis of data mining and data analytics is to be used. Aside from current SCADA data, historical meteorological and life-cycle data also enter this concept. In addition, the innovate system is not restricted to a single turbine or wind farm, but is to particularly allow the linking of further wind farms. Through the additionally available data and information, a comprehensive picture of the individual icing risk of each observed turbine can be calculated. Here, the location properties as well as those of the turbine– such as type, height, installed rotor blade, etc. are to be taken into account.
The methods derived toward the identification of important parameters provide for an efficient process control of the wind farm and/or individual turbines. Through this comprehensive approach including interconnectivity, it will be possible in the future to recognize the risk of icing at an early stage and minimize the effects to individual wind farms and individual turbines.