电力系统自动化2013，Vol.37Issue(4)：92-97,6.DOI:10.7500/AEPS201111169
基于Hadoop的广域测量系统数据处理
Data Processing of Hadoop-based Wide Area Measurement System
摘要
Abstract
To solve the wide area measurement system (WAMS) mass data processing problems such as data redundancy and low processing efficiency, a cloud computing platform based on Hadoop is designed and implemented.The structure of this platform is described first.Then, a WAMS mass data loading method is designed based on Hadoop distributed file system (HDFS) and parallel data extraction-transformation-loading (ETL) for multiple file processing by using MapReduce.MPApriori data mining algorithm combined with MapReduce is proposed to discover the interplay of power sites when cascading failures occurred.Finally, through the regional network WAMS actual data processing, the effectiveness of mass data processing on Hadoop is proven.This platform is suitable for mass power grid files data mining by high performance local area network connection of a computer cluster.关键词
云计算/数据处理/广域测量系统/MapReduceKey words
cloud computing/ data processing/ wide area measurement system (WAMS)/ MapReduce引用本文复制引用
曲朝阳,朱莉,张士林..基于Hadoop的广域测量系统数据处理[J].电力系统自动化,2013,37(4):92-97,6.基金项目
国家自然科学基金资助项目(51077010) （51077010）
吉林省自然科学基金资助项目(20101517). （20101517）
