Lisa Vernesoni
Statistical modeling of SCADA data for reliable wind resource assessment: The case of Leitwind wind turbine.
Rel. Giovanni Bracco, Gianfranco Chicco. Politecnico di Torino, Master of science program in Energy And Nuclear Engineering, 2025
Abstract
In the context of wind energy expansion, wind resource assessment is traditionally based on meteorological masts, which require extensive pre-installation campaigns and involve substantial costs. Furthermore, their deployment is limited in spatial coverage, as masts are often dismantled after the completion of measurement campaigns, resulting in temporally and spatially constrained site data. Recent approaches have explored the use of Supervisory Control and Data Acquisition (SCADA) systems for project monitoring and development, owing to their greater availability and the existence of longer-term datasets. To date, SCADA data have been primarily employed for performance evaluation and anomaly detection, with limited application in wind resource assessment due to data confidentiality and access restrictions.
Moreover, wind speed and direction measured at the nacelle are inherently affected by rotor-induced flow distortion, nacelle geometry, and turbine operating conditions (such as rotor speed, pitch angle, and yaw misalignment), which introduce measurement biases in resource assessment
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