The rise in renewable power generation leads invariably to increased volatility in power grids, requiring more detailed modeling of grid constraints and more frequent solving of forecasted overloads while minimizing societal costs of required redispatching actions. This presents a business-critical dynamic optimization challenge for system operators . Congestion Management and Optimisation for System Operators, e.g. for solving forecasted overloads within the transmission network. The goal is to define the optimal preventive re-dispatching actions and transformer settings required to avoid overloads and ensure an adequate grid operation. In System Operations, difficulties are mainly present in the form of increasing solving times or loss of accuracy when dealing with complex calculations using classical computing solvers. Complexity arises from several factors: - General development towards more detailed modelling of renewables and conventional generators, as well as grid constraints and optimisation variables - Tight process timings due to short-term nature of operational planning and realtime operation with a renewable driven system - Complex market movements and operational constraints