A Fault Line Selection Method for Small Current Grounding System Based on Big Data

被引：0

作者：

Shao, Zheng ^{[1
]}

Wang, Liancheng ^{[1
]}

Zhang, Han ^{[2
]}

机构：

[1] Shandong Univ, Sch Elect Engn, Jinan, Peoples R China

[2] Hefei Univ Technol, Sch Elect Engn & Automat, Hefei, Peoples R China

来源：

2016 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC) | 2016年

关键词：

small current grounding system; single-line-to-ground(SLG) faults; fault line selection; big data; data mining; simulation;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The fault mechanism of small current grounding system for single-line-to-ground (SLG) faults and the functions of big data techniques are discussed. A new fault line selecting method for SLG faults based on big data theory is proposed. The method resolves the problem of detecting fault lines by making use of a mass of data from the grid wh ich consists of both electrical and non-electrical quantities. Some unstructured data is preprocessed to feature information of faults, and data mining techniques are used to learn the complex non linear mapping relation between data and fault lines. Whenever a new grounding fault occurs, the mapping relation can be used to select the fault line. The sm all current grounding system is modeled by simulation software PSCAD and data is analyzed by a software package MATLAB and SPSS Modeler, and the result shows that this method works effectively and improves the accuracy offault line selection.

引用

页码：2470 / 2474

页数：5

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