Wind Turbine Static Errors Related to Yaw, Pitch or Anemometer Apparatus: Guidelines for the Diagnosis and Related Performance Assessment

Davide Astolfi (), Silvia Iuliano, Antony Vasile, Marco Pasetti, Salvatore Dello Iacono and Alfredo Vaccaro
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Davide Astolfi: Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy
Silvia Iuliano: Department of Engineering, University of Sannio, Piazza Roma 21, 82100 Benevento, Italy
Antony Vasile: Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy
Marco Pasetti: Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy
Salvatore Dello Iacono: Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy
Alfredo Vaccaro: Department of Engineering, University of Sannio, Piazza Roma 21, 82100 Benevento, Italy

Energies, 2024, vol. 17, issue 24, 1-34

Abstract: The optimization of the efficiency of wind turbine systems is a fundamental task, from the perspective of a growing share of electricity produced from wind. Despite this, and given the complex multivariate dependence of the power of wind turbines on environmental conditions and working parameters, the literature is lacking studies specifically devoted to a careful characterization of wind farm performance. In particular, in the literature, it is overlooked that there are several types of faults which have similar manifestations and that can be defined as static errors. This kind of error manifests as a static bias occurring from a certain time onward, which can affect the anemometer, the absolute or relative pitch of the blades, or the yaw system. Static or systematic errors typically do not cause the functional failure of the wind turbine system, but they deserve attention due to the fact that they cause power production loss throughout the operation time. Based on this, the first objective of the present study is a critical review of the recent papers devoted to three types of wind turbine static errors: anemometer bias, static yaw error, and pitch misalignment. As a result, a comprehensive viewpoint, enhancing the state of the art in the literature, is developed in this study. Given that the use of data collected by Supervisory Control And Data Acquisition (SCADA) systems has, up to now, been prevailing for the diagnosis of systematic errors compared to the use of further specific sensors, particular attention in the present study is thus devoted to the discussion of the phenomena which can be observable through SCADA data analysis. Based on this, finally, a rigorous work flow is formulated for detecting static errors and discriminating among them through SCADA data analysis. Nevertheless, methods based on additional information sources (like further sensors or meteorological data) are also discussed. An important aspect of this study is that, for each considered type of systematic error, some previously unpublished results based on real-world SCADA data are reported in order to corroborate the proposed framework. Summarizing, then, the present is the first paper which considers and discusses several types of wind turbine static errors in a unified viewpoint, correctly interprets apparently controversial results collected in the literature, and finally provides guidelines for the diagnosis of this kind of error and for the quantification of the performance drop associated with their presence.

Keywords: wind power; wind turbines; performance analysis; static errors; systematic errors; condition monitoring; SCADA data analysis; yaw; pitch; anemometer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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