The increasing contribution of variable weather dependent renewable energy sources (RES) to the electricity grids of European countries challenges the existing energy system in many ways. Resilient power grid and power plant management as well as viable trading at power stock exchanges are the two most obvious and known concerns which must be guaranteed even under conditions of volatile and insufficiently predictable wind and solar power. The challenge of delivering continuous probabilistic short term forecasts can be achieved by ultra-large ensemble sizes with O (1000) model runs, yielding probability density functions (pdfs) for wind and clouds respectively. At sufficient (1km) resolution this ultimately requires exascale capability, which in turn means addressing a series of technical challenges, particularly in the areas of ensemble modelling, programming models, and big data analytics. The flagship framework for accommodating these innovations will be the Ensemble for Stochastic Interpolation of Atmospheric Simulations, which will initially include the Weather Research and Forecast (WRF) model adopted to predict winds at rotor hub heights and cloud optical thickness (COT). The EURopean Air pollution Dispersion-Inverse Model (EURAD-IM) will further address the impact of aerosol-induced turbudity on solar power production. These tools will provide the meterological data needed for wind and solar day-ahead power forecasting, as well as for short-term forecasting in confluence with satellite-based cloud-motion solvers.