EWEA technology workshop, Bilbao 2016

EWEA technology workshop, Bilbao 2016

Sereema will present how to apply smart sensors technology to improve the analysis of operating wind turbines.


Smart sensors technology allows to easily add capacities to operating wind turbines in order to optimize their maintenance and increase their AEP in a cost effective way. Smart sensors rely on the Internet of Thing infrastructure to provide added value and ready to use information to the End User so that the correct actions can be determined and conducted. To exemplify the potential of this new approach to the diagnosis of operating wind turbines, we present a study case of rotor balance monitoring using a connected device placed on the wind turbine.

The benefits of using IoT technologies for the rotor balance studies when compared to the classic measurements procedures are, among others: a continuous surveillance versus a punctual measurement, the capacity to determine and select the perfect conditions for the analysis and the ability to provide highly integrated information as well as detailed data when needed. Four wind turbines (1.7 MW rated power) were equipped with the connected-smart sensing device with embedded accelerometers and firmware adapted to the rotor balance analysis.

The continuous surveillance permits the definition of a baseline behavior and threshold levels adapted to each turbine. The adapted algorithms provide the identification of rotor imbalances (aerodynamic and masse imbalances) and their evolution with time. The results are based on 10 minutes periods with the perfect conditions for the analysis. On average over one hundred 10 minutes periods are studied per month and per wind turbine to provide a high confidence level diagnosis of the rotor balance.

The final result of this process is an automated, on-line diagnosis of the rotor balance of all equipped wind turbines. The ready to use information on the status of the wind turbines is accessible through the internet for operators and maintenance teams.

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