Discussion of Wind Turbine Performance Based on SCADA Data and Multiple Test Case Analysis

Davide Astolfi, Ravi Pandit, Ludovico Terzi and Andrea Lombardi
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Davide Astolfi: Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Ravi Pandit: Centre for Life-Cycle Engineering and Management (CLEM), School of Aerospace Transport and Manufacturing, Cranfield University, Bedford MK43 0AL, UK
Ludovico Terzi: ENGIE Italia, Via Chiese, 20126 Milano, Italy
Andrea Lombardi: ENGIE Italia, Via Chiese, 20126 Milano, Italy

Energies, 2022, vol. 15, issue 15, 1-17

Abstract: This work is devoted to the formulation of innovative SCADA-based methods for wind turbine performance analysis and interpretation. The work is organized as an academia–industry collaboration: three test cases are analyzed, two with hydraulic pitch control (Vestas V90 and V100) and one with electric pitch control (Senvion MM92). The investigation is based on the method of bins, on a polynomial regression applied to operation curves that have never been analyzed in detail in the literature before, and on correlation and causality analysis. A key point is the analysis of measurement channels related to the blade pitch control and to the rotor: pitch manifold pressure, pitch piston traveled distance and tower vibrations for the hydraulic pitch wind turbines, and blade pitch current for the electric pitch wind turbines. The main result of this study is that cases of noticeable under-performance are observed for the hydraulic pitch wind turbines, which are associated with pitch pressure decrease in time for one case and to suspected rotor unbalance for another case. On the other way round, the behavior of the rotational speed and blade pitch curves is homogeneous and stable for the wind turbines electrically controlled. Summarizing, the evidence collected in this work identifies the hydraulic pitch as a sensible component of the wind turbine that should be monitored cautiously because it is likely associated with performance decline with age.

Keywords: wind energy; wind turbines; performance; power curve; SCADA; data analysis; blade pitch (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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