基于Hadoop平台的电力统计不良数据高效识别方法研究

Research on high efficiency identification method of bad data in power statistics based on Hadoop platform

针对智能电网不断发展背景下,电力系统运行中受到各种因素干扰导致的不良数据问题,提出了基于Hadoop平台的电力统计不良数据高效识别方法。对文中研究背景进行分析,设计开源Hadoop平台和分布式文件系统结构,对MapReduce计算模型流程进行分析。针对Hadoop中的MapReduce实现的流程设计电力统计不良数据的识别算法,对大数据进行充分挖掘,提出数据辨识和修正,并且对提出的算法进行仿真分析。通过仿真结果表示,文中方法能够解决不良数据问题,提高辨识算法精确度。

In view of the problem of bad data caused by various factors in the operation of power system under the background of the continuous development of smart grid,an efficient identification method of bad data in power statistics based on Hadoop platform is proposed.This paper analyzes the research background,designs the open source Hadoop platform and distributed file system structure,and analyzes the MapReduce computing model process.Aiming at the process of MapReduce in Hadoop,the paper designs an algorithm to identify the bad data of power statistics,fully mine the big data,propose data identification and correction,and simulate the algorithm.The simulation results show that the method can solve the problem of bad data and improve the accuracy of identification algorithm.