Application of Postprocessing for Renewable Energy

Abstract Renewable energy generation capacities are being deployed at a rapid pace, now reaching a total of more than 800 GW worldwide, if adding up generation capacities for wind and solar power. Power generation from those sources is tightly linked to weather conditions, hence making renewable energy forecasting tightly linked to meteorological forecasting. Even though probabilistic forecasts of renewable power generation still often rely on deterministic weather forecasts, ensemble forecasts will necessarily be an increasing trend in order to issue the most complete information for future power generation. The basic and key concepts of postprocessing ensemble weather forecasts for renewable energy applications are described and discussed here, based on the example of wind power generation. These include the conversion of ensemble weather forecasts to power and generation of calibrated forecast products. Finally, perspectives regarding future developments in this area are given.