:In order to qualify the fluctuating nature of solar radiation under tropical climate, we classify daily distributions of the clearness index k t by estimating a finite mixture of Dirichlet distributions without assuming any parametric hypothesis on these daily distributions. The method is applied to solar radiation measurements performed in

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Abstract. We consider here wind speed time series and the aggregate output wind power from a wind farm. We study their scaling statistics in the framework of fully developed turbulence and Kolmogorov's theory. We estimate their Fourier power spectra and consider their scaling properties in the physical space. We show that the atmospheric wind speed and the aggregate power output from a wind farm are intermittent and multifractal over a wide range of scales. The coupling between simultaneous data of the wind speed and aggregate power output is investigated through a joint multifractal description using the generalized correlation functions (GCFs). This multiscaling test is compatible with a linear relation between the wind speed and the aggregate power output fluctuations for timescales T 10 3 s 15 min.

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The correlation between the flow turbulence and the performances of a marine current turbine is studied. First, the incoming flow encountered in the flume tank is characterized in the framework of fully developed turbulent cascades in the inertial range. The Reynolds number, the Kolmogorov dissipation scale and the integral scale, are estimated from flow measurements. The intermittency of the turbulence is characterized in the lognormal multifractal framework, and the influence of the turbulent flow on the turbine power is assessed. The rotor speed control unit characteristics used for the turbine regulation induces non-negligible effects on the turbine behavior under fluctuations loads. Even if the power spectrum does not reveal any scale invariance, a multiscale analysis allows us to show the correlations between the turbulence time series and the power produced. The classical Mean Square Coherency function shows that for scales larger than 10 s, the upstream velocity and power have large correlations. In the framework of the Empirical Mode Decomposition method, such correlations are studied using the time-dependence intrinsic correlation analysis method. This method allows to zoom into time-frequency scales where the flow perturbations induced some modifications in power production. Highlights ► A high sampling rate of a turbulent flow velocity highlights its multiscale properties. ► There is no power law in the power production Fourier spectrum. ► The intermittency degree of flow velocity increases behind the marine current turbine. ► The coherency is higher in the lower frequencies and reach its minimum at 1 Hz. ► Local correlation analysis spotted a pattern on the loss of correlation.