The liberalization of the European energy market posed novel and challenging problems for transmission system operators. Moreover, due to the increasing shares of renewable energy sources related to the transition towards a fossil-free energy system, system operators have to cope with increasing spatial and temporal variability of supply and demand. Still, they have to ensure that all energy transport demands are fulfilled. In addition, the transport of new fuels such as ammonia or hydrogen need to be integrated. Decision support systems provide the means to address these challenges.

The goal of the prescriptive analytics group is to model complex energy networks and develop fast algorithms for optimized decision support for robust operations.     

Due to their underlying technical and physical processes, energy network optimization problems are nonlinear and nonconvex, and some of the control decisions are discrete. Appropriate mathematical modeling leads to large mixed-integer nonconvex problems, which usually cannot be solved by standard solvers.

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 include optimizing the network flow in large networks as well as computing accurate control decisions for complex junctions of the system, e.g., compressor stations in gas networks, for short term operational decision making. Since our custom-tailored solutions are highly dependent on energy network-specific knowledge, we collaborate closely with partners from the gas industry and several other research institutes.