AI-Driven Fault Detection in Electrical Networks: Applications Explored in the Periodic Series of Technological Studies
Abstract
This work aims at the recent application of technological innovations towards the implementation of AI-enabled fault detection systems in electrical networks. It poses an appropriate methodology for the application of machine learning algorithms within real time monitoring and control systems. Consequently, precision and responsiveness in detection and response were greatly improved compared to results obtained from previous attempts. In comparison with cutting-edge systems, the analysis undertaken suggests that there are indeed real deficits of concentration regarding automated maintenance and predictive resiliency augmentation of the system AI focus zones. The conclusions are useful for network dependability enhancement and smart grid technologies development.
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