The Research And Implementation Of Fault Diagnosis Service For Smart Grid Fault Analysis System

In the background of Smart Grid, the Fault Analysis System is in full swing. The work of this paper is mainly about the core of this system -- the research and implementation of fault diagnosis service.The smart substation based on IEC 61850 has an integrated systematic organizational structure and support system, which is the basis of the realization of advanced applications such as Fault Analysis System. This paper overviews the related problems firstly.Then it is detailed introduced the process of primary and protection equipments modeling and imported into In-Memory Database, which is the stage of data preparation. Based on the topology information in the In-Memory Database and the data collected from the pre-collection equipment, the fault area is demarcated through grid topology analysis. After demarcating the fault area, the diagnosis method of optimization model is used at primary station, which generates the result format XML. This paper improves the model in order to reduce the false diagnosis rate under the premise of no missing one.Because of the fault diagnosis algorithm based on relay protection and breaker only has its inborn defects, it is a tendency to make information fusion with fault record data in order to enhance the effect of diagnosis. This paper introduces the information fusion theory in detail and makes a little improvement. The fusion is accomplished on both characteristic and decision layer.In the characteristic layer fusion, with the help of wavelet techniques, the firing sequence of Fuzzy Petri net can be extracted from fault record data. The substation fault diagnosis results as well as evaluation of the operations of protections and breakers are obtained through FPN calculation. Then a brief fault report is generated and sent to the primary station, which is used to revise the telesignal data.In the decision layer fusion, it defines three indicators, which is specially designed for line diagnosis. Different data processing methods are used to translate the optimization and wavelet analysis results into the support degree of components. Considering the possibility of multi-failure, it defines a frame of recognition for each element, revising the traditional method which adds up all of the components to one. Based on DS evidence theory improved by this paper, the aforementioned evidences are fused with optimization result. The turnkey solution can eliminate fault line diagnosis of optimization method, which is proved based on Real Time Digital System (RTDS).