A substation fault diagnosis method based on IEC61850

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.

I. Introduction

Substations play an important role in power systems. When a fault occurs in a substation, a flood of alarm information could be displayed without any analysis on the console in the control center, and lead to the difficulty for dispatchers to identify the faulted section in a short time. Therefore, an accurate and efficient method of fault diagnosis in substation is significant for rapid fault location and hence assures the stability and security of power system. So far, the presented approaches mainly includes Expert Systems (ES) [1]–[2], analytic model based approaches [3]–[6], Artificial Neural Networks (ANN) [7]–[9], Petri Nets[10], [11], Rough Set [12] and so on.