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Cited 10 time in webofscience Cited 16 time in scopus
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A Novel Load Image Profile-Based Electricity Load Clustering Methodology

Authors
Park, Keon-JunSon, Sung-Yong
Issue Date
May-2019
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Class load image profile; clustering; data processing; image processing; load image profile; load profile
Citation
IEEE ACCESS, v.7, pp.59048 - 59058
Journal Title
IEEE ACCESS
Volume
7
Start Page
59048
End Page
59058
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/2874
DOI
10.1109/ACCESS.2019.2914216
ISSN
2169-3536
Abstract
An in-depth understanding of consumer energy consumption patterns is essential for accurate forecasting and efficient management. In this paper, a novel load profile analysis methodology is proposed using an image processing technology that simplifies the understanding and improvement of electricity consumption patterns. The electricity consumption patterns over time are represented as load image profiles in two dimensions. These profiles are modified by image processing using filtering and thresholding techniques to suppress excessive sensitivity. Subsequently, the clustering algorithms are performed to classify the load image profiles, and representative class load image profiles are obtained. The resulting clusters are compared to the results of conventional load profile analysis. The proposed methodology shows enhanced performance over the conventional approach from the viewpoint of evaluation among the different load image profile classes.
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Son, Sung Yong
Graduate School (Dept. of Next Generation Smart Energy System Convergence)
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