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.

International audienceThere is growing efforts for the development of wind energy. Yet, as for other renewable resources, a basic characteristic of wind energy is to deliver intermittent power. In this paper, we consider this topic by analyzing data provided by the wind industry. We discuss first the spectral properties of the data and the corresponding power curve. We estimate the scaling behavior in the inertial scale of wind input and the power output. We also study the rotor revolution scaling fluctuations. Finally the wind/power transfer function is studied, together with the wind/rotation and rotation/power intermediary transfer functions

The massive integration of sustainable energies into electrical grids (non-interconnected or connected) is a major problem due to their stochastic character revealed by strong fluctuations at all scales. In this paper, the scaling behaviour or power law correlations and the nature of scaling behaviour of sustainable resource data such as flow velocity, atmospheric wind speed, solar global solar radiation and sustainable energy such as, wind power output, are highlighted. For the first time, Fourier power spectral densities are estimated for each dataset. We show that the power spectrum densities obtained are close to the 5/3 Kolmogorov spectrum. Furthermore, the multifractal and intermittent properties of sustainable resource and energy data have been revealed by the concavity of the scaling exponent function. The proposed analysis frame allows a full description of fluctuations of processes considered. A good knowledge of the dynamic of fluctuations is crucial to management of the integration of sustainable energies into a grid.