电力系统自动化Issue(7)：138-144,7.DOI:10.7500/AEPS20140111003
基于时间序列分析的输变电设备状态大数据清洗方法
Cleaning Method for Big Data of Power Transmission and Transformation Equipment State Based on Time Sequence Analysis
摘要
Abstract
Data cleaning is a key step in data preprocessing for state assessment of power equipment to help improve data quality and utilization.As the device status information can be made equivalent to the multivariate time sequence of each state,an iterative data cleaning method based on time sequence analysis is proposed.First,the abnormal data in time sequence is classified with the missing values treated as one of the types of the anomalies.Then the impact of different types of anomalies on the sequential model is quantified and several implementation steps of the iterative method are described.Finally,the approach is tested on the on-line monitoring data of a power equipment of the China Southern power grid.The results show that this method is capable of not only effectively identifying the abnormal data,but also repairing the noise points and missing values in meeting the data cleaning requirement.关键词
大数据/数据清洗/时间序列/电力设备状态数据Key words
big data/data cleaning/time sequence/state data of power equipment引用本文复制引用
严英杰,盛戈皞,陈玉峰,江秀臣,郭志红,秦少鹏..基于时间序列分析的输变电设备状态大数据清洗方法[J].电力系统自动化,2015,(7):138-144,7.基金项目
国家自然科学基金资助项目(51477100) （51477100）
国家高技术研究发展计划(863计划)资助项目(SS2012AA050803) （863计划）
国家电网公司科技项目.@@@@This work is supported by National Natural Science Foundation of China （No.51477100），National High Technology Research and Development Program of China（863 Program）（No.SS2012AA050803）and State Grid Corporation of China （）
