Application Research of Edge Algorithms for Privacy Protection in Distribution Network Fault Diagnosis Systems

With the development of smart grids, distribution network fault diagnosis systems play a crucial role in ensuring the stable operation of power systems. However, traditional centralized diagnostic methods face issues such as data privacy breaches and low computational efficiency. This paper proposes a novel method that applies privacy protection algorithms based on edge computing to distribution network fault diagnosis systems. By deploying privacy protection algorithms at edge nodes, the method achieves distributed fault diagnosis and local data processing, significantly improving computational efficiency and data security. Experimental results show that this method ensures high diagnostic accuracy while substantially reducing data transmission volume and the risk of privacy breaches. This research provides a new solution for the secure and efficient operation of smart grids.