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The Journal of Engineering
Article . 2019 . Peer-reviewed
License: CC BY
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The Journal of Engineering
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License: CC BY
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Abnormal behaviour analysis algorithm for electricity consumption based on density clustering

Authors: Min Xiang; Huayang Rao; Tong Tan; Zaiqian Wang; Yue Ma;

Abnormal behaviour analysis algorithm for electricity consumption based on density clustering

Abstract

How to effectively detect abnormal electricity consumption behaviour from a large‐scale electrical load data is very important to smart grid. An abnormal electricity consumption analysis method based on density clustering is proposed. First, the similar users located in fix area are clustered in accordance with the electricity consumption characteristics. Then, on the basis of electricity consumption data sequence, the outlier electricity consumption for the similar users are obtained with density clustering. The matching degrees of these outliers can be calculated based on the similar user electricity consumption model and historical electricity consumption model. Finally, according to the threshold value, the abnormal electricity consumption can be discriminated with the comprehensive support degree. The simulation results show that this method can effectively identify the abnormal electricity consumption behaviour.

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Keywords

abnormal behaviour analysis algorithm, power engineering computing, similar user electricity consumption model, similar users, load forecasting, pattern clustering, outlier electricity consumption, power consumption, electricity consumption characteristics, historical electricity consumption model, large-scale electrical load data, Engineering (General). Civil engineering (General), electricity consumption data sequence, abnormal electricity consumption analysis method, density clustering, abnormal electricity consumption behaviour, TA1-2040

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    popularity
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    Top 10%
    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Average
gold