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The Design of Distributed Power Big Data Analysis Framework and Its Application in Residential Electricity Analysis

机译:分布式电力大数据分析框架设计及其在住宅电力分析中的应用

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With the development of digital, information and intelligent process of power system, more and more data sources appear. The traditional standalone environment has been difficult to adapt to the need of the analysis of massive data. The power industry also needs to use real-time database, distributed storage and indexing, data mining and other technologies to achieve massive data storage and data mining. In this paper, a distributed power big data platform, which integrates storage, calculation, mining and analysis functions, is constructed based on the requirement of power industry for mass heterogeneous data processing and analysis. Then, we use Apriori algorithm to analyze residential electricity data based on the big data platform. The experimental results show that the distributed computing framework can greatly improve the efficiency of data processing. At the same time, using data mining technology to analyze residential electricity data can help us find the distribution and change rules of electric load and improve load forecasting ability.
机译:随着电力系统的数字,信息和智能过程的发展,出现了越来越多的数据源。传统的独立环境难以适应对大规模数据分析的需要。电力行业还需要使用实时数据库,分布式存储和索引,数据挖掘等技术来实现大规模的数据存储和数据挖掘。本文基于对质量异构数据处理和分析的电力行业的要求,构建了一种分布式电力大数据平台,该平台集成了存储,计算,采矿和分析功能。然后,我们使用APRiori算法根据大数据平台分析住宅电力数据。实验结果表明,分布式计算框架可以大大提高数据处理的效率。同时,使用数据挖掘技术来分析住宅用电数据可以帮助我们找到电负载的分布和改变规则,提高负载预测能力。

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