In many countries, the energy sector continues to undergo substantial changes due to the expansion of renewable energy sources (RES). This expansion necessitates an extensive structural rearrangement of the power system with the power grid taking center stage. While today’s power grid infrastructure has been designed for centralized and controllable power generation in conventional power plants, the RES expansion leads to an increasingly uncertain, volatile and decentralized generation.

In order to ensure a dependable grid operation, methods are needed, which are able to consider a high resolution of regional and temporal input data. Inevitably, this requirement leads to a target conflict between model complexity and computational intensity on the one hand and model accuracy on the other hand. It is therefore a central challenge to provide efficient methods for power grid optimization, including an accurate consideration of non-linear and non-convex alternating current power flow constraints.

In cooperation with our partners at the Karlsruhe Institute of Technology, EMCL addresses the central challenge to provide efficient optimization methods for Dynamic Optimal Power Flow (DOPF) problems. The main focus of our research lies in:

• Mathematical modeling of Dynamic Optimal Power Flow problems
• Development of new linear solvers that are specialized for DOPF and which enable the use of HPC systems
• Development of model reduction strategies for DOPF