Estimation of Turbulence Intensity from Cup Anemometer-Based Mean Wind Speed Data via Fractal Interpolation

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Abstract

In the well-known process of the turbine design, turbulence intensity (TI) plays a vital role in prediction of the power output and loads on the turbine's structure. TI is believed to be an important statistical parameter of the wind speed that can be extracted from the signals recorded by the dedicated sensors in the wind energy area. Despite the limitations of the mast-mounted sensors, they are probably more popular than LIDARs in wind energy applications. Although the sonic anemometers are reference tools in measuring turbulent features of wind, they are expensive instruments to be employed in a large-scale. In this regard, the cup anemometers appear to be the most commonly used instruments in the wind energy community. Accordingly, it would be tremendously advantageous if the 1-Hz cup anemometer data can be employed with the synthetic down-scaling idea to build the turbulence-like velocity signal fields. In this research, small-scale fluctuations are constructed via the Fractal Interpolation (FI) technique. In addition, this study aims to assess the compatibility of the FI technique in enhancing the cup anemometer data. The analysis has been carried out for the data collected in September 2018. Through this analysis, it is deduced that the cup anemometer data can be improved using the FI method. Subsequently, by applying the FI method, in most of the cases, the standard deviation values of the cup anemometer data are increased.

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