Research on Power Grid Fault Diagnosis Based on Artificial Intelligence

In order to avoid the expansion of power accidents and reduce fault losses, it is necessary to improve the power grid fault diagnosis, based on this point, this paper introduces artificial intelligence technology to explore the power grid fault diagnosis system and proposes a power grid fault diagnosis method based on deep belief network structure. The electrical quantities such as current and voltage of each phase directly after the fault occurs are used as the original input, and the fault state characteristics are automatically learned and extracted from the original time domain signals, thus enabling the identification of fault types. The experimental results show that the method has significantly improved over traditional fault diagnosis in terms of fast fault response, accurate diagnosis and localization, reliable decision support and non-manual intervention.