Title :
A substation fault diagnosis method based on IEC61850
Author :
Gao Zhanjun; Wang Junshan; Gao Nuo
Author_Institution :
Key Laboratory of Power System Intelligent Dispatch and Control (Shandong University), Ministry of education, Jinan, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
Substations play an important role in power systems. The application of the IEC61850 standard changes the situation of the traditional substation greatly. The information in the intelligent substation is rich, but it is difficult for the operators to digest them in a short time without an effective assistant tool. A fault diagnosis method which uses the alarming information of the primary and secondary system of the intelligent substation is proposed in this paper. This method first uses the Bayesian based algorithm to find the possible faulty set H1. And at the same time, the information entropy difference algorithm is used to obtain the fault assumption set H2. Then the fault assumption set H2 is used to calculate the fault correctness and a decision fusion algorithm can locate the fault components accurately. Finally, a fault scenario is served for demonstrating the feasibility and validity of the method presented.
Keywords :
"Tin","Jacobian matrices","Substations","Artificial intelligence","Monitoring","Switches"
Conference_Titel :
Power & Energy Society General Meeting, 2015 IEEE
DOI :
10.1109/PESGM.2015.7286171