In the course of the expansion of regenerative energy systems, a decentralized distribution of power plants is inevitable. Electricity cannot always be generated as desired, in the vicinity of conurbations with increased electricity demand, since production is linked to external influences. For example, the electricity generated in offshore wind farms has to be transported to consumers over long distances.

High-voltage direct current (HVDC) transmission is of key importance for the transport of electricity over long distances. Compared to conventional three-phase transmission, the energy loss decreases as the transmission distance increases. For the transmission of direct current, the alternating currents of the grid must be converted. This is done with the aid of Modular Multilevel Converters (MMC), which are very attractive for direct current transmission due to their modularity and the large number of voltage levels. With MMCs, the output voltages can be scaled and an almost sinusoidal voltage curve can be realized.

Conventional control methods for MMCs are designed only over a narrow operating range and the performance of the converters decreases significantly when this range is left. This project, funded by the German Research Foundation (DFG), aims to design a novel control method based on nonlinear model predictive control (MPC). This ensures optimal operation of the HVDC system over the entire operating range. In addition, the controller bandwidth is to be increased in order to react quickly to grid disturbances. Furthermore, with MPC the cell capacities can be reduced and line filters can be dispensed with, which results in a cost reduction of the overall system.