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The Power of Big Data and Data Analytics for AMI Data: A Case Study

机译:大数据和AMI数据的数据分析功能:案例研究

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摘要

In recent years, there has been a transformation in the value chain of different industrial sectors, like the electricity networks, with the appearance of smart grids. Currently, the underlying knowledge in raw data coming from numerous devices can mark a significant competitive advantage for utilities. It is the case of the Advanced Metering Infrastructure (AMI). Such technology gets user consumption characteristics at levels of detail that were previously not possible. In this context, the terms big data and data analytics become relevant, which are tools that allow using large volumes of information and the generation of valuable knowledge from raw data that can support data-driven decisions for operating on the grid. This paper presents the results of the big data implementation and data analytics techniques in a case study with smart metering data from the city of London. Implemented big data and data analytic techniques to show how to understand user consumption patterns on a broader horizon, the relationships with seasonal variables identify behaviors related to specific events and atypical consumptions. This knowledge helps support decision making about improving demand response programs and, in general, the planning and operation of the Smart Grid.
机译:近年来,随着智能电网的出现,不同工业部门(如电力网络)的价值链发生了转变。当前,来自众多设备的原始数据中的基础知识可以标志着公用事业的巨大竞争优势。高级计量基础结构(AMI)就是这种情况。这种技术使用户消费特性达到了以前不可能达到的细节水平。在这种情况下,大数据和数据分析这两个术语变得相关,这是允许使用大量信息并从原始数据生成有价值的知识的工具,这些数据可以支持在网格上进行数据驱动的决策。本文以伦敦金融城的智能计量数据为例,介绍了大数据实施和数据分析技术的结果。实施大数据和数据分析技术以展示如何在更广阔的视野中了解用户的消费模式,与季节性变量的关系可以识别与特定事件和非典型消费相关的行为。这些知识有助于支持有关改进需求响应计划以及总体而言智能电网的计划和运营的决策。

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