Intelligent fault area identification in distribution networks: a joint graph convolutional network approach

Key Points

• To develop a method for identifying fault areas in distribution networks using a joint graph convolutional network approach.
• Utilized graph convolutional networks for data analysis.
• Analyzed network topology to enhance fault identification accuracy.
• Implemented joint learning techniques for improved performance.
• Significantly improved accuracy in fault area identification compared to traditional methods.
• Reduced response time to faults in distribution networks.
• Demonstrated effectiveness across various network conditions.