Application of Artificial Intelligence in Fault Detection and Isolation of Power System

As a complex network, the reliability and stability of power system are very important to social economy and people's life. Artificial intelligence (AI) technology, including expert system, artificial neural network (ANN), Petri net, etc., significantly improves the accuracy and efficiency of power system fault detection by simulating human intelligence, and realizes automatic fault isolation. In this study, a fault detection and isolation (FDI) model based on AI is constructed. Through deep learning algorithm, especially convolutional neural network (CNN), the characteristics of power system operation data are extracted and fault classification is realized, and fast and accurate fault detection is realized. In addition, combined with the power system topology and fault detection results, an intelligent algorithm is designed to realize rapid fault location and automatic isolation. Experimental results show that AI model is superior to traditional methods and support vector machine (SVM) in fault detection accuracy, location speed and isolation efficiency, with an accuracy of 98.5%, an average isolation time of 0.2 seconds and a success rate of 98%. This study provides a theoretical and practical basis for the intelligent transformation of power system, and is helpful to improve the efficiency and security of power system operation and maintenance.