Multi dimensional intelligent interaction method for distribution network fault information based on similarity clustering and regularization

In order to ensure the stable operation of the power grid, a multi-dimensional intelligent interaction method for distribution network fault information based on similarity clustering and regularization is proposed. Use reachability matrix to analyze the connectivity status of the network in depth. By regularizing certain parameters or variables during the constraint clustering process, thereby improving the accuracy and stability of the clustering results. Combined with the set distribution network fault information exchange system, the accurate positioning of the distribution network fault section is achieved by calculating the current of the distribution network fault line, and the multi-dimensional intelligent exchange of distribution network fault information is completed. The experimental results show that the information similarity clustering effect of the proposed method is close to 1, and the localization accuracy remains above $\mathbf{9 8 \%}$ when facing different distribution network faults. The proposed method can effectively reflect the fault information of the distribution network and ensure the effective operation of the distribution network.