Automatic extraction of basic electricity consumption patterns in household

Haoyang Shen, H. Hino, N. Murata, S. Wakao, Y. Hayashi
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引用次数: 2

Abstract

Electricity consumption in households varies dependent on a lot of possible reasons such as lifestyle, family configuration, and weather. It is of great importance to optimize the electricity generation system to install for each household. In our previous work, we proposed a clustering approach for extracting a small number of basic electricity consumption patterns in a household. In this study, we apply the method to a larger dataset with many households. In the previous work, we determined the number of basic patterns in a heuristic manner. In this work, we use gap statistics to automatically determine an appropriate number of basic patterns, and we obtained a reasonable result on a large-scale data.
家庭基本用电模式自动提取
家庭用电量的变化取决于许多可能的原因,如生活方式、家庭结构和天气。为每个家庭优化发电系统的安装是非常重要的。在我们之前的工作中,我们提出了一种聚类方法来提取家庭中少量的基本电力消耗模式。在本研究中,我们将该方法应用于包含许多家庭的更大数据集。在之前的工作中,我们以启发式的方式确定了基本模式的数量。在这项工作中,我们使用差距统计来自动确定适当数量的基本模式,并在大规模数据上获得了合理的结果。
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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