Energy Meteorology: FORECASTING

FORECASTING

Forecast of Solar Irradiance

Forecasting of solar irradiance will become a major issue in the future integration of solar energy resources into existing energy supply structures. Due to the strong impact of cloudiness on surface irradiance the description of the temporal development of the cloud situation is essential for irradiance forecasting. As a measure of cloudiness, cloud index images according to the Heliosat method are calculated from METEOSAT images. A statistical method was used to derive motion vector fields from two consecutive images. The future image then is determined by applying the calculated motion vector field to the actual image. As far as short-term time horizons (up to 2h) are concerned, this method leads to high quality information about radiation with excellent temporal and spatial resolution. For mid-term time horizons (up to 1-2 days) mesoscale models, e.g. MM5, will be used in addition to the motion vector fields method.

Meteosat-8 in space

Forecast of Wind Energy

Accurate forecasting of the wind resource up to two days ahead is recognised as a major contribution for reliable large-scale wind power integration. Especially, in a liberalised electricity market, prediction tools enhance the position of wind energy compared to other forms of dispatchable generation.
The ANEMOS project aims to develop advanced forecasting models that will substantially outperform current methods. Emphasis is given to situations like complex terrain, extreme weather conditions, as well as to offshore prediction for which no specific tools currently exist.
More details of ANEMOS on the project homepage: anemos.cma.fr

Information on Previento - A Tool for Wind Power Forecasting - developed at the University of Oldenburg is available here: PREVIENTO

Contact

Dr. Detlev Heinemann
Energy and Semiconductor Research Laboratory
Institute of Physics - University of Oldenburg
D-26111 Oldenburg, Germany
Tel: +49 441 - 798 3543
Fax: +49 441 - 798 3326
e-mail: detlev.heinemann@uni-oldenburg.de