Lisa Reis

• The rapid growth in offshore wind brings various challenges to power system research and industry, such as the development of multi-terminal multi-vendor HVDC grids. To ensure interoperability in those power converter dominated systems, suitable models are needed to efficiently perform stability and interaction studies. With state-space based small-signal methods stability and interaction phenomena can be assessed globally for a complex system. Yet detailed models are needed. However, in multi-vendor projects most likely only black-boxed models will be available to protect the intellectual property, so that identification techniques are necessary to obtain suitable models. This thesis contributes to the research activities on statespace model identification of black-boxed power electronic systems. In the first part of the thesis, a method was developed and tested, where the matrix elements of linearized state-space models were fitted in dependency of the operating point, based on input sweeps performed on the model of a grid forming power converter controlled as a virtual synchronous machine. It was discussed how changes in multiple inputs can be approximated by the superposition of the individual input dependencies and a fully operating point dependent state-space model approximation was created. The results were validated in time and frequency domain analyses. It was found that the method can provide a good approximation, especially for the operating range around the default operating point. In the second part, identification of a power electronic system was performed based on measurement data which was generated experimentally from a low voltage laboratory system. A sequence of input perturbations was applied to the laboratory system and frequency response data was calculated from the corresponding output perturbations. The data served as basis for model identification with N4SID and a soon to be published vector fitting method. The identified models were validated by a visual inspection of the transfer function and by comparison of the calculated step responses to the step responses measured in the laboratory. It was found that the treatment of incomplete data sets, the generation of substitute data and the impact of time delays on the identification might be worth further investigation. This work provides a valuable contribution to the research of state-space model identification of black-boxed power electronic systems. It points out challenges and presents promising approaches to enable state-space based methods for stability analysis and interaction studies in future multi-terminal multi-vendor HVDC grids.