Application of data analytics for information retrieval from a typical DSO's database

J. Ponoćko, J. Milanović, R. Preece, N. C. Woolley
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Abstract

This paper introduces the reasons for big data analytics in distribution network studies and potential benefits it could give. Summary of the most common data mining methods used in power system studies is also given, followed by a comparative analysis. A use case is shown at the end in order to present some examples of extraction of useful information from raw data stored in a real distribution utility's database. This was done by using some of the basic data mining methods applied to different types of attributes describing distribution system feeders in 11 kV and 6.6 kV network. The initial results showed that the usefulness of information depends on the level of data aggregation, as well as the choice of data analytics method.
数据分析在典型DSO数据库信息检索中的应用
本文介绍了在配电网研究中使用大数据分析的原因及其可能带来的好处。总结了电力系统研究中常用的数据挖掘方法,并进行了比较分析。最后展示了一个用例,以展示从存储在实际分布公用事业数据库中的原始数据中提取有用信息的一些示例。这是通过使用一些基本的数据挖掘方法来实现的,这些方法应用于描述11 kV和6.6 kV网络中配电系统馈线的不同类型属性。初步结果表明,信息的有用性取决于数据聚合的水平,以及数据分析方法的选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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