System-based fault locator based on a pattern recognition approach - Meyer, Janick; Dimopoulos, Ioannis; Jäger, Johann (IEEE Power and Energy Society General Meeting, 2020)
The fast detection of a fault location is an important task in power grids to ensure system security at all. Todays protection relays are particular challenged by multivariate grid structures caused by volatile renewable infeeds. This paper presents an innovative strategy to use an Artificial Neural Network (ANN) for accurate fault location determination under all grid and fault conditions.The measurement results of several relays installed in the grid form a unique pattern for each fault condition, which an ANN is able to learn and recognize. This makes it possible to investigate faults on transmission lines that are not even protected by distance protection relays.The approach is validated with an adapted version of the IEEE 9 bus test power grid, where faults on various locations with different fault resistances were considered. The outcome is discussed and the effectiveness compared with the results of conventional protection relays.
CRIS-Team Scopus Importer:2021-04-19
Keywords: Artificial Intelligence; Deep Neural Network; Distance Protection Relay; Fault Locator; Protection System