Abstract
To locate the fault location accurately and solve the problem quickly is the key to improve the power supply capacity of power grid. This paper presents a fault location method based on SVM fault branch selection algorithm and similarity matching. Firstly, an SVM-based fault branch filter classifier was constructed based on the positive sequence component feature matrix data of each monitoring point, which can accurately select the branch where the current fault is located. Then, based on the positive sequence voltage distribution characteristics, the Euclidean distance and Pearson correlation coefficient (PCC) are used to establish the similarity objective function of fault location. And then, the fault is accurately located by the objective function. Finally, the proposed method is validated by using an IEEE-14 node network. The results show that the proposed method is effective and accurate.
Highlights
Fast and accurate location of distribution network faults can effectively reduce the time of troubleshooting and blackout, reduce economic losses, and improve power supply reliability [1,2,3,4,5]
Scholars have done a lot of work on the accurate fault location of the distribution network. e main fault location methods are mainly divided into the traveling wave method and nontraveling wave method. e traveling wave method [8,9,10] determined the fault distance by measuring the propagation time of voltage and current traveling wave to the fault point
The monitoring devices required for traveling wave positioning are expensive, and the practical application of engineering is difficult. e impedance method [11] calculated the impedance of the fault branch by measuring the voltage and current at the fault point, and calculated the fault distance
Summary
Fast and accurate location of distribution network faults can effectively reduce the time of troubleshooting and blackout, reduce economic losses, and improve power supply reliability [1,2,3,4,5]. Most of the existing location methods either fail to overcome the influence of transition resistance on the location results or need to know the fault branch and fault type to locate, or the location results are greatly affected by measurement errors and fake fault points or need to traverse all locations of the network to search fault points, which results in a huge amount of calculation when the system scale is large To solve these problems, a fault location method based on the SVM fault branch selection and similarity model matching was proposed in this paper. The symmetrical component method is used to decompose the positive sequence component, and the positive sequence component is used to analyze the fault
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