Small-Scale Prediction of Wind Energy in a Scale Invariant Framework

The intermittency of wind turbine power is an important issue limiting the massive development of this renewable energy. To address this issue, we consider the theoretical framework of multifractal energy cascades, which is a classical framework for describing and characterizing the fluctuations in the turbulent wind input. The multi-scaling statistics of the input turbulent wind are inherited by the wind power produced, and these multi-scaling statistics correspond to a memory in the process. There is memory coming from the fact that the Hurst scaling exponent is smaller than 1/2, and memory coming from the scale invariant cascade process generating intermittency. This memory can be exploited for prediction purposes. Here we test an approach based on an analogy of the power scaling properties with a fractional brownian motion. This is illustrated on real exploitation systems.