Comparison of methods for the identification of mesoscale wind speed fluctuations

Abstract

Mesoscale wind speed fluctuations influence the characteristics of offshore wind energy. These recurring wind speed changes on time scales between tens of minutes and six hours lead to power output fluctuations. In order to investigate the meteorological conditions associated with mesoscale wind speed fluctuations, a measure is needed to detect these situations in wind speed time series. Previous studies used the empirical Hilbert-Huang Transform to determine the energy in the mesoscale frequency range or calculated the standard deviation of a band-pass filtered wind speed time series. The aim of this paper is to introduce newly developed empirical mesoscale fluctuation measures and to compare them with existing measures in regard to their sensitivity to recurring wind speed changes. One of the methods is based on the Hilbert-Huang Transform, two on the Fast Fourier Transform and one on wind speed increments. It is found that despite various complexity of the methods, all methods can identify days with highly variable mesoscale wind speeds equally well.