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Electrical power and energy compensation demand with regard to topological restrictions of German mains for an efficient operation of smart grids

: Beyer, D.; Karstädt, F.; Fischer, B.; Agsten, M.; Bretschneider, P.


Institute of Electrical and Electronics Engineers -IEEE-, Power & Energy Society -PES-:
3rd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies, ISGT Europe 2012 : 14 - 17 October 2012 Berlin, Germany
Piscataway, NJ: IEEE, 2012
ISBN: 978-1-4673-2596-7
ISBN: 978-1-4673-2595-0
ISBN: 978-1-4673-2597-4
8 pp.
International Conference and Exhibition on Innovative Smart Grid Technologies - Europe (ISGT Europe) <3, 2012, Berlin>
Conference Paper
Fraunhofer IOSB ()
energy storage; distributed generation; topological orientated grid model; grid balancing; volatile energies

This paper introduces two newly developed gird models, which are topological orientated and make it capable to study the impact of decentraliced volatile energy generation on the German transmission and distribution grid. With these models it is possible to determine the electrical power and energy compensation demand of the German mains for different energy studies and at the same time investigations regarding to the topological restrictions of the electrical grid and the primary operating resources can be made. The methodical procedure of creating the German electrical transmission and distribution grid models is presented and the database is described. A case studie, for an exemplary region in Germany with the two topological orientated grid models, is performed for different time horizons of an energy lead scenario and shows the electrical power and energy compensation demand, as well as it is showing the restrictions of the grid and the operating resources. It is made clear that the developed models and approaches can be used for deriving optimal locations for energy storages and also to determine the dimensioning of these storages. Furthermore the developing and validation of smart energy management systems can be enhanced by integrating and simulating within the proposed models.