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Storage and Indexing of Big Data for Power Distribution Networks

机译:配电网络大数据的存储和索引

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With the construction of power distribution networks, a large amount of various types of data has accumulated, including automation and information technology system data as well as customer power consumption data, including distribution transformer, distribution transformer station, distribution switch station, meter, and electrical energy quality. The storage and index association of a large amount of different data is the basis for big data analysis. As a massive type of time-series data, customer power consumption load includes large-scale customers and high-density data collection. To improve the efficiency of query and analysis, this study proposed time-series data indexing technology to reduce the time required for data query and retrieval, to improve the efficiency of time-series data analysis, and to enable power companies to deeply analyze and cluster the power consumption behaviors of their customers.
机译:随着配电网络的构造,大量各种类型的数据积累,包括自动化和信息技术系统数据以及客户功耗数据,包括配电变压器,配电变压器站,分配交换站,仪表和电气能量质量。大量不同数据的存储和索引关联是大数据分析的基础。作为一种大规模的时间序列数据,客户功耗负载包括大规模客户和高密度数据收集。为了提高查询和分析效率,本研究提出了时序数据索引技术,减少了数据查询和检索所需的时间,提高时间序列数据分析的效率,并使电力公司能够深深分析和集群。客户的功耗行为。

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