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Fakultät für Elektrotechnik und Informationstechnik
Third Party Projects


Analysis of future grid loads under consideration of uncertainties for application in risk-based grid design

The integration of renewable energy systems , the simultaneous reduction of conventional power plants, the increase in load due to sector coupling and the liberalization of the energy markets result in significant uncertainties in the future electrical energy system and therefore in the load on the electrical energy networks. The uncertainties currently existing can be classified into two levels. First, they concern the future design or development of generation, consisting of conventional power plants and regenerative sources, and the loads (stage one). Here, the uncertainty relates both to the amount of installed capacity depending on the energy source and to the local allocation influenced by the economic efficiency of existing power plants, raw material price developments, area potentials and sector coupling. Secondly, there are a number of new uncertainties for each generation park design when operations are taken into account (level two). These include, for example, CO2 certificate prices, market designs, weather conditions, uncertainties regarding developments in neighbouring European countries and the design of operational options such as redispatch, regulation concepts and flexibility.

Due to long horizons for planning power lines and cables, investment decisions for grid expansion have to be made under these uncertain future developments. In order to ensure a reliable and secure energy network in the future, it is necessary to model and consider these uncertainties entirely and adequately in the decision-making process. This requires a detailed mathematical-statistical analysis and quantification of the uncertainties including their correlations. Based on this, the effects on the load flow have to be determined with methods of probabilistic load flow calculation (prob. LF). Subsequently, the results serve to be used for grid planning and to make a methodologically substantiated decision under uncertainty.


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