Design and Research of an Electric Power System Reliability Evaluation Model Based on Artificial Intelligence Algorithms

This paper addresses the complexity and uncertainty issues encountered during the operation of electric power systems by proposing a reliability evaluation model based on artificial intelligence algorithms. First, an analysis of conventional evaluation methods is conducted to explore their limitations in handling large-scale, multivariable data. Subsequently, multiple artificial intelligence algorithms, such as neural networks and support vector machines, are introduced, and preprocessing and feature extraction are carried out on actual operating data from electric power systems. A multi-level, modular model structure is then designed and simulated on an experimental platform, with comparative analysis against traditional methods. The results demonstrate that the proposed model exhibits significant advantages in terms of accuracy, robustness, and real-time performance, thereby providing an effective solution for reliability evaluation in electric power systems. Finally, this paper discusses the shortcomings of the model regarding parameter optimization and practical application, and proposes directions for future improvements.