Design of Intelligent Fault Location System for Distribution Lines Based on Multi-feature Combination

Distribution network feeder fault location based on multi-feature joint judgment is an important content of distribution automation, which has a great impact on improving power supply reliability. Due to the wide distribution of multi-featured distribution networks, it is difficult to achieve effective positioning. Therefore, the research on automatic positioning method of distribution network feeder with multiple features and its realization equipment has important engineering practical significance. In this paper, the K-fault diagnosis method of analog circuit diagnosis is applied to feeder fault location based on the characteristics of multi-featured feeder faults in the distribution network, and its specific implementation scheme in feeder fault location is described. In this paper, based on the characteristics of multi-featured distribution network lines, a wireless sensor network is researched and designed. The sensors installed on the distribution line complete the collection and preprocessing of voltage, current and other information, and the collected synchronization data. The information is transmitted to the monitoring center through the wireless communication network, and the monitoring center analyzes and processes the information. This article realizes the fast determination of the fault location. A 10 kV cable line model was established, and the feasibility of the program was simulated and analyzed using Matlab. The results show that the program can accurately determine the location of the ground fault according to the change of the zero-sequence current amplitude, and solve the traditional fault location technology. Problems such as long time and poor positioning effect have high application value for the fault location of cable lines with multi-features in a large range. The experimental results show that when a small metallic resistance is used for grounding, when a large ground signal flows, the measured signal is 1.5 mA. The same reason and method can gradually reduce the measurement range and finally determine the fault point.