Key points are not available for this paper at this time.
This paper analyzes the application of Artificial Intelligence (AI) for intelligent monitoring and early warning systems in electric power safety. The ever-increasing demand for a secure and reliable electrical grid necessitates advancements in preventative measures. AI offers a novel approach by utilizing machine learning and deep learning algorithms to analyze the vast amount of sensor and video data collected across the power grid. These algorithms can identify subtle anomalies and patterns that signal potential equipment degradation, impending faults, or unsafe conditions. By issuing timely warnings, AI-powered systems can prevent catastrophic failures, optimize maintenance schedules through predictive capabilities, and ultimately enhance the safety of power grid personnel. However, implementing these intelligent systems necessitates addressing specific challenges. Data quality and comprehensiveness are paramount for effective AI model training and operation. Seamless integration with existing power grid monitoring infrastructure requires meticulous planning and execution with accuracy of 96.3%.
Feng Zhang (Fri,) studied this question.