Model-based protection system for fault detection and location in converter-fed networks

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The decarbonization of the electrical energy supply leads to a massive expansion of infeed-systems based on renewable energies into the electrical grid. Regenerative energy systems are dependent on sufficient energy storage and energy transport capacity. From today's perspective, this can only be implemented with power electronic converters. Power converters are therefore increasingly determining the operating and fault behavior of future networks. In the distribution grids, localized network structures will emerge that are completely dominated by power converters.The high flexibility potential of the converter control, particularly in terms of fault behavior, as well as the high structural variance of the grids, pose insolvable problems for classic network protection concepts and thus endanger network security.In the proposed research project, we pursue a fundamentally new approach to model-based protection systems. This consistently develops the known approaches of model-based equipment protection to model-based grid protection. The first-time use of Kalman filters in this context as both state and parameter estimators improves the functionality and flexibility of the developed method compared to previous model-based approaches and increases the necessary robustness. A close interlinking of protection and predictive control procedures of the converters promises synergy effects with regard to the detection of fault scenarios that are difficult to identify. The new approach is to be implemented on a laboratory sample and tested on a real-time network simulator (RTDS).With the implementation of this research project, an important contribution can be made to more grid security in future converter-dominated networks.