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Electric Load Classification by Binary Voltage-Current Trajectory Mapping

delete2016-01-01
delete105
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OA
AI
L
Liang Du *
何
何大伟 (Dawei He)
R
Ronald G. Harley
T
T.G. Habetler
DOI:10.1109/TSG.2015.2442225delete
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摘要

摘要

En 中文
Characterization of electric loads provides opportunities to incorporate detailed energy usage information into applications such as protection, efficiency certification, demand response, and energy management. This paper proposes a low computational cost, but yet accurate method, to extract signatures for load classification and characterization. Instead of utilizing digital signal processing and frequency-domain analysis, this paper abstracts the similarity of voltage-current (V-I) trajectories between loads and proposes to map V-I trajectories to a grid of cells with binary values. Graphical signatures can then be extracted for many applications. The proposed method significantly reduces the computational cost compared with existing frequency-domain signature extraction methods. Test results show that an average of over 99% of success rate can be achieved using the proposed signatures.
Keyword:
Load classification
load identification
load signatures
nonintrusive load monitoring (NILM)
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期刊

IEEE Transactions on Smart Grid 封面图
IEEE Transactions on Smart Grid
IF:
9.8
论文数:
5.7K
被引数:
4.3W

机构

U
university system of georgia
学者数:
7.3W
论文数: 6.6W
被引数: 101
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