Gerhard Gesell

WISENT: e-Science for Energy Meteorology

Our energy production increasingly depends on renewable energy sources, which impose new challenges for distributed and decentralized systems. One problem is that the availability of renewable energy sources such as wind and solar is not continuous as it is affected by meteorological factors. The challenge is to develop forecast methods capable of determining the level of power generation in near real-time in order to control power plants for optimal energy production. Another scenario is the identification of optimal locations for such power plants. In our collaborative project, these tasks are investigated in the domain of energy meteorology. For that purpose large data sources from many different sensors (e.g., satellites and ground stations) are the base for complex computations. The idea is to parallelize these computations in order to obtain significant speedup. This paper reports on an ongoing project employing Grid technologies in that context. Our approach to processing large data sets from a variety of heterogeneous data sources as well as ideas for parallel and distributed computing in energy meteorology are presented. Preliminary experience with several Grid middleware systems in our application scenario is discussed.

Verification of sectoral cloud motion based direct normal irradiance nowcasting from satellite imagery

The successful integration of solar electricity from photovoltaics or concentrating solar power plants into the existing electricity supply requires an electricity production forecast for 48 hours, while any improved surface irradiance forecast over the next upcoming hours is relevant for an optimized operation of the power plant. While numerical weather prediction has been widely assessed and is in commercial use, the short-term nowcasting is still a major field of development. European Commission’s FP7 DNICast project is especially focusing on this task and this paper reports about parts of DNICast results. A nowcasting scheme based on Meteosat Second Generation cloud imagery and cloud movement tracking has been developed for Southern Spain as part of a solar production forecasting tool (CSP-FoSyS). It avoids the well-known, but not really satisfying standard cloud motion vector approach by using a sectoral approach and asking the question at which time any cloud structure will affect the power plant. I...