Open AccessResearch and Application of Power Information Risk Early Warning System Based on Big Data
Author(s) -
Zhenying Tang,
Yunzhu An,
Ziqian Li,
Liyang Xu,
Fan Li,
He Wang
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/558/5/052065
Subject(s) - computer science , database transaction , warning system , automation , data collection , electric power system , scale (ratio) , big data , risk analysis (engineering) , information system , data science , reliability engineering , database , data mining , power (physics) , engineering , business , telecommunications , mechanical engineering , statistics , physics , mathematics , electrical engineering , quantum mechanics
With the increase of power equipment and business systems and the increasing complexity of IT system architecture and operation scale, the existing manual operation and maintenance mode can no longer meet the needs of business. This paper proposes an electric power information risk early warning system based on big data, which analyzes operation and maintenance data from five angles of transaction analysis, trend analysis, comparative analysis, composition analysis and comprehensive analysis. The system consists of three parts: data collection, data management, data analysis and risk early warning. By improving the operation and maintenance automation level, the system security level and operation efficiency are greatly improved.