An operational data-driven malfunction detection framework for enhanced power distribution system monitoring - the DeMaDs approach

The changes in the electric energy system toward a sus-tainable future are inevitable and already on the way to-day. This often entails a change of paradigm for the elec-tric energy grid, for example, the switch from central to decentralized power generation which also has to provide grid-supporting functionalities. However, due to the scar-city of distributed sensors, new solutions for grid opera-tors for monitoring these functionalities are needed. The framework presented in this work allows to apply and as-sess data-driven detection methods in order to implement such monitoring capabilities. Furthermore, an approach to a multi-stage detection of misconfigurations is intro-duced. Details on implementations of the single stages as well as their requirements are also presented. Further-more, testing and validation results are discussed. Due to its feature of being seamlessly integrable into system op-erators' current metering infrastructure, clear benefits of the proposed solution are pointed out.