Due to the challenges posed by the energy transition, i.e., the volatility of renewable energies and the increasing electrification due to the rise of electric vehicles and heat pumps, it is increasingly important to identify critical states in low-voltage grids. The paper investigates the suitability of the Extended Kalman-Filter for state estimation in low voltage grids by implementing and analyzing its application in a real grid. The results demonstrate that voltage can be reliably estimated in real-time and show that the Extended Kalman-Filter is a suitable method in terms of computational efficiency, adaptability, and data dependency.