The energy sector witnesses major structural challenges due to EU liberalization of energy markets and the changeover to renewable energy sources. In order to meet these challenges, large investments are necessary which of course should be as cost-effective as possible. Moreover, the new regulations lead to more complex planning and operation processes for which existing methods are no longer appropriate. The goal of this working group is to develop novel mathematical models and solutions methods capable to cope with the increasing complexity of energy networks.

Energy optimization problems are often-due to their underlying technical and physical processes-nonlinear and nonconvex, and some of the control decisions are of discrete nature. An appropriate mathematical modelling leads to large mixed-integer nonconvex problems which usually cannot be solved by standard solvers. Uncertainty regarding supply and demand is another challenge that has to be taken into account. For foresighted decision support we develop forecast models for supply and demands. Moreover, the behavior of other market participants may also have an impact. Therefore, models feature both stochastic and game-theoretic components.

Due to the inherent mathematical difficulties, effective mathematical solution methods have to be custom-tailored to the problems to be solved. Core competences of the group range from long term capacity and extension planning to short term operational desicion making. Currently, we are developing methods for foresighted decision support for the operation of one of the largest gas transmission networks of Germany. Since our custom-tailored solutions are highly dependent on energy network specific knowledge, we collaborate closely with partners from gas industry and several other research institutes.