Fault Diagnosis Techniques for Electrical Distribution Network Based on Artificial Intelligence and Signal Processing: A Review
Yunyu Cao, Jinrui Tang, Shaohui Shi, Defu Cai, Li Zhang, Ping Xiong
Abstract
This paper provides a comprehensive and systematic review of fault diagnosis methods based on artificial intelligence (AI) in smart distribution networks described in the literature. For the first time, it systematically combs through the main fault diagnosis objectives and corresponding fault diagnosis methods for a smart distribution network from the perspective of combined signal processing and artificial intelligence algorithms. The paper provides an in-depth analysis of the advantages and disadvantages of various signal processing techniques and intelligent algorithms in different fault diagnosis tasks, focusing on the impact of different data dimensions on the effect of fault diagnosis. This paper points out that data security issues and the question of how to combine expert domain knowledge with artificial intelligence technology are essential directions for the future development of fault diagnosis in smart distribution network.