Fault Location Based on Bayes Probability Likelihood Ratio for Distribution Networks
WANG Ying-ying, LUO Yi, TU Guang-yu (Huazhong University of Science and Technology, Wuhan 430074, China)
Based on Bayes probability likelihood ratio, a new fault location algorithm for distribution networks is proposed. A fault diagnosis model is established firstly, and then by using the fault information sequence gathered by the SCADA system from load switches, the probability likelihood ratios are calculated using the algorithm proposed. Finally, by searching the maximal fault probability, the fault section in distribution networks can be identified and isolated, in which the error and aberrance of SCADA information are screened to a certain extent. As a practical method, the SCADA information based fault location method can quickly determine the fault location. Examples are given to verify its correctness and effectiveness.
【CateGory Index】： TM711