Data Mining-based Method for Screening Transient Fault Detection Information of a Distribution System
In order to improve the effect and shorten the execution time of screening false,invalid and redundant information,the paper presents a data mining-based method for screening transient fault detection information of a power distribution system.Based on the analysis of the transient fault detection mechanism of a distribution system,the types of the collected transient fault detection information are determined.The data mining algorithm is used to collect the initial transient fault detection information in the form of layer-by-layer search iteration,fuse the transient fault detection information,and identify the false,invalid and redundant information.According to the identification results,the transient fault detection information of the distribution system is screened by the means of dynamic deletion.The results show that the average redundancy degree and invalid data percentage of the proposed method are 1.57％and 1.87％,respectively.The proposed method outputs screening results with lower redundancy and invalid data ratio indices and less execution time.It is concluded that this method has obvious advantages in both screening effect and operational performance.
data miningdistribution systemstransient fault detection informationinformation screenin
万方数据
维普
