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Effective Self Attention Modeling for Aspect Based Sentiment Analysis Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Profiling of Household Residents’ Electricity Consumption Behavior Using Clustering Analysis

Authors : Christian Nordahl, Veselka Boeva, Håkan Grahn, Marie Persson Netz

Published in: Computational Science – ICCS 2019

Publisher: Springer International Publishing

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Abstract

In this study we apply clustering techniques for analyzing and understanding households’ electricity consumption data. The knowledge extracted by this analysis is used to create a model of normal electricity consumption behavior for each particular household. Initially, the household’s electricity consumption data are partitioned into a number of clusters with similar daily electricity consumption profiles. The centroids of the generated clusters can be considered as representative signatures of a household’s electricity consumption behavior. The proposed approach is evaluated by conducting a number of experiments on electricity consumption data of ten selected households. The obtained results show that the proposed approach is suitable for data organizing and understanding, and can be applied for modeling electricity consumption behavior on a household level.

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Metadata
Title
Profiling of Household Residents’ Electricity Consumption Behavior Using Clustering Analysis
Authors
Christian Nordahl
Veselka Boeva
Håkan Grahn
Marie Persson Netz
Copyright Year
2019
Book
Computational Science – ICCS 2019

Print ISBN: 978-3-030-22749-4

Electronic ISBN: 978-3-030-22750-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-22750-0_78

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