Disastrous Data Fusion Method Based on Dempster-Shafter Evidence Theory for Smart Gri
Chunqi Chang · Journal of Information and Computational Science · 2014
Smart grid has the powerful ability of self-healing and self-adaption. It can timely predict faults and disasters by analyzing and processing the detected data from sensors of the power grid before faults and disasters emerge. In order to improve the detection accuracy and reduce the redundant information, data fusion technology is introduced to process sensor data of smart grid. In this paper, Dempster-Shafter (D-S) evidence theory is applied to smart grid disaster predicting, two data fusion methods based on D-S evidence theory are proposed. The paper gives the data fusion framework of smart grid, then based on it presents the two data fusion methods in details, nally compares their performance by simulation test.