Seasonal forecasting of wind energy resource and production in France and associated risk.

Summary The increase in the share of intermittent renewable energies in the energy mix is generating problems related to the predictability of electricity production. In particular, on a seasonal basis, transmission system operators are forced to project the availability of generation resources and forecast demand. This allows them to guarantee supply for the next winter or summer. Nevertheless, current projections are mainly based on historical data (climatology) of temperatures (consumption), winds (wind production), or solar radiation (photovoltaic production). The thesis presents four works: three in the framework of seasonal forecasting, and one study on the realism of surface wind as modeled by the European Center's weather forecasting model.If wind energy forecasting at short time scales ranging from minutes to days as well as wind tendency at climatic scales have been widely studied, wind production forecasting at intermediate time scales ranging from a fortnight to the season has received little attention. The predictability of mid-latitude weather at these distant horizons is indeed still an open question. However, several studies have shown that seasonal numerical forecasting models are able to provide information on the variability of large-scale atmospheric circulation through the prediction of large-scale circulation oscillations, such as ENSO in the Pacific, or the NAO in the North Atlantic. It has also been shown that these oscillations have a strong impact on precipitation, temperature, and surface wind. Building the relationship between these indicators of large-scale atmospheric circulation and surface wind in France can therefore take into account the interannual variability of surface wind, which is not capable by definition climatology. This is the idea developed in the 3 studies concerning seasonal forecasting. In order to forecast the wind resource and production on a seasonal scale, two probabilistic models are developed. One is parametric, based on the prediction of the seasonal distribution of surface wind at different locations in France. The other is non-parametric, based on the estimation of the probability density of daily surface wind conditional on the state of the atmosphere. The third study proposes to reconstruct the joint probability of French national consumption and production, thus allowing to measure the risk of imbalance between supply and demand.