Distribution fault location using graph neural network with both node and link attributes
Abstract:
Systems and methods performed by a fault detection apparatus for fault detection and localization in distribution feeders having branches and nodes. The method including receive feeder raw data in a feeder of a power system. Process the feeder raw data with given operational electrical characteristics of the feeder to generate a branch attribute dataset for each branch separated by a pair of nodes for all branches. Generate a node attribute dataset for each node for all the nodes in the feeder. Input the branch and node attribute datasets into a trained neural network to determine whether a branch has a fault and a fault location within the branch, to output a classification of the fault and the fault location. Generate an alert signal based upon determining the classified fault and fault location in response to the alert signal to an outage response system.
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