Characterizing the Wake Effects on Wind Power Generator Operation by Data-Driven Techniques

Davide Astolfi, Fabrizio De Caro and Alfredo Vaccaro ()
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Davide Astolfi: Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Fabrizio De Caro: Department of Engineering, University of Sannio, Piazza Roma 21, 82100 Benevento, Italy
Alfredo Vaccaro: Department of Engineering, University of Sannio, Piazza Roma 21, 82100 Benevento, Italy

Energies, 2023, vol. 16, issue 15, 1-19

Abstract: Wakes between neighboring wind turbines are a significant source of energy loss in wind farm operations. Extensive research has been conducted to analyze and understand wind turbine wakes, ranging from aerodynamic descriptions to advanced control strategies. However, there is a relatively overlooked research area focused on characterizing real-world wind farm operations under wake conditions using Supervisory Control And Data Acquisition (SCADA) parameters. This study aims to address this gap by presenting a detailed discussion based on SCADA data analysis from a real-world test case. The analysis focuses on two selected wind turbines within an onshore wind farm operating under wake conditions. Operation curves and data-driven methods are utilized to describe the turbines’ performance. Particularly, the analysis of the operation curves reveals that a wind turbine operating within a wake experiences reduced power production not only due to the velocity deficit but also due to increased turbulence intensity caused by the wake. This effect is particularly prominent during partial load operation when the rotational speed saturates. The turbulence intensity, manifested in the variability of rotational speed and blade pitch, emerges as the crucial factor determining the extent of wake-induced power loss. The findings indicate that turbulence intensity is strongly correlated with the proximity of the wind direction to the center of the wake sector. However, it is important to consider that these two factors may convey slightly different information, possibly influenced by terrain effects. Therefore, both turbulence intensity and wind direction should be taken into account to accurately describe the behavior of wind turbines operating within wakes.

Keywords: wind energy; wind turbines; wakes; data analysis; SCADA; condition monitoring (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: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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