Research on big data risk assessment of major transformer defects and faults fusing power grid, equipment and environment based on SVM

2017 3rd International Conference on Environmental Science and Material Application

生态环境科学;材料科学

Guo, Lijuan^1 ; Yan, Haijun^1 ; Gao, Wensheng^2 ; Chen, Yun^2 ; Hao, Yongqi^3

Guangxi Electric Power Research Institute, Nanning, China^1

School of Electrical Engineering, Tsinghua University, Bejing, China^2

School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China^3

关键词: Environment data;    Evaluation results;    Large data analysis;    Main transformer;    Potential law;    Power grid equipment;    Power grids;    Power System;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/108/5/052027/pdf
DOI  :  10.1088/1755-1315/108/5/052027

来源: IOP

【 摘 要 】

With the development of power big data, considering the wider power system data, the appropriate large data analysis method can be used to mine the potential law and value of power big data. On the basis of considering all kinds of monitoring data and defects and fault records of main transformer, the paper integrates the power grid, equipment as well as environment data and uses SVM as the main algorithm to evaluate the risk of the main transformer. It gets and compares the evaluation results under different modes, and proves that the risk assessment algorithms and schemes have certain effectiveness. This paper provides a new idea for data fusion of smart grid, and provides a reference for further big data evaluation of power grid equipment.