聚类框架在英国国内电力数据中的应用

Ian Dent, U. Aickelin, T. Rodden
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引用次数: 19

摘要

英国电力行业将很快获得大量来自家庭家庭的数据,这篇论文是朝着从非侵入性家庭电力监测中获得有用信息迈出的一步。本文采用了一种方法聚类国内负载概况,已成功地在葡萄牙使用,并将其应用于英国的数据。发现葡萄牙工作中的首选技术(结合自组织地图和Kmeans的过程)不适合英国数据。这项工作使用了1990年左右在米尔顿凯恩斯收集的数据,并表明可以确定家庭集群,这表明定义比电力行业目前公布的两种负荷概况更刻板的用电模式是适当的。这项工作是一个更广泛的项目的一部分,该项目成功地应用需求侧管理技术,使整个电网受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of a Clustering Framework to UK Domestic Electricity Data
The UK electricity industry will shortly have available a massively increased amount of data from domestic households and this paper is a step towards deriving useful information from non intrusive household level monitoring of electricity. The paper takes an approach to clustering domestic load profiles that has been successfully used in Portugal and applies it to UK data. It is found that the preferred technique in the Portuguese work (a process combining Self Organised Maps and Kmeans) is not appropriate for the UK data. The work uses data collected in Milton Keynes around 1990 and shows that clusters of households can be identified demonstrating the appropriateness of defining more stereotypical electricity usage patterns than the two load profiles currently published by the electricity industry. The work is part of a wider project to successfully apply demand side management techniques to gain benefits across the whole electricity network.
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