Online Fault Prediction Based on Collaborative Filtering in Smart Grid

Smart grid, responsible for upgrading traditional power networks by integrating with cutting-edge information and communication networks, forms coupled networks but also pose potential hazards in the face of fault cascade. In coupled networks, fault prediction is of significance because tight interaction between power nodes and communication nodes makes the smart grid more vulnerable. Unfortunately, most existing works of fault prediction are specific to a single network and do not consider the correlation of coupled elements. To address these limitations, in this paper, we highlight the interdependence of networks and define fault correlation. Further, we propose a probabilistic prediction model using collaborative filtering in machine learning. We finally present an online prediction algorithm. We conduct experiments to illustrate the effectiveness of our prediction algorithm with different parameters and give some observations that may give more insight into interdependent networks.