Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information

In power systems, failures of vulnerable lines can trigger large-scale cascading failures, and vulnerability assessment is dedicated to locating these lines and reducing the risks of such failures. Based on a structure and attribute network embedding (SANE) algorithm, a novel quantitative vulnerability analysis method is proposed to identify vulnerable lines in this research. First, a two-layered random walk network with topological and electrical properties of transmission lines is established. Subsequently, based on the weighted degree of nodes in the two-layered network, the inter-layer and intra-layer walking transition probabilities are developed to obtain walk sequences. Then, a Word2Vec algorithm is applied to obtain low-dimension vectors representing transmission lines, according to obtained walk sequences for calculating the vulnerability index of transmissions lines. Finally, the proposed method is compared with three widely used methods in two test systems. Results show the network embedding based method is superior to those comparison methods and can provide guidance for identifying vulnerable lines.