The Simulation Of Single-phase Earthed Fault In Small Current System And Multi-information Line Selection Study

The single-phase ground fault accounted for 80% of all distribution networks' fault. How to accurately, rapidly diagnosis fault lines is a practical issues and also a problem in the face of electrical engineers to be resolve promptly. The current of small-current system is so little that could be easily affected by the environment changes and the influence parameters of itself. Nowadays, a lot of researchers put forward many principles to solve this problem while any method has its limitation. In recent years, with the development of computer and electronic technology, the transient fault signal can be quickly acquired which makes accurate line selection possible. The single method of line selection cannot satisfy the needs of fault line selection. With the development and application of intelligent control theory, the comprehensive analysis of the fault information greatly improves the accuracy of line diagnosis which was called multi-information line selection.Firstly, this paper gives briefly conception of small-current system and emphatically analyzes three different operation of single-phase earthed process, including current and voltage changes. Both transient and steady information of earthed fault are analysis. Then the method of line selection is introduced. In order to further understanding of earthed fault, the simulation model of small current system was built based on MATLAB. A lot of simulation was found according to the actual failure. By analysis and comparison of the figure, the influence factors of fault information are appearing. The results of simulation and comprehensive of fault signal contribute to the multi-information research. Otherwise based on MATLAB platform it develops the GUI interfaces which can automatic built simulation model.Another difficulty of fault line selection lies in the fault information's extraction and comprehensive judgment. In this paper, the fifth harmonic of zero-sequence current, line's power and energy of the zero-sequence current are used as the fault feature. Based on the three characteristics and BP neural network, the multi-information line selection was operation. From test, the BP neural network has very good learning ability and the sinulination result is satisfied. The multi-information line selection method is much batter than the single line selection methods.