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Development of Automatic Voltage Stabilization System for Substation Using Deep Learning

Authors
Moon, JiyongSon, MinyeongOh, ByeongchanJin, JeongpilKim, KwangilShin, Younsoon
Issue Date
Jan-2022
Publisher
Springer Verlag
Keywords
Capacity prediction; Voltage stabilization system
Citation
Innovative Computing, v.935 LNEE, pp 133 - 134
Pages
2
Indexed
SCOPUS
Journal Title
Innovative Computing
Volume
935 LNEE
Start Page
133
End Page
134
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/3842
DOI
10.1007/978-981-19-4132-0_14
ISSN
1876-1100
1876-1119
Abstract
The voltage adjustment process is currently done manually by resident staff. As such, voltage regulation based on human judgement not only entails great uncertainty about voltage stabilization but also makes efficient operation in consideration of the economic feasibility of power facilities impossible. Therefore, this paper proposes an automatic voltage stabilization system that can automatically perform voltage adjustment. The proposed system predicts the required input capacity, and then predicts the optimal adjustment method considering the efficiency of power facility operation by adding an optimization process. In addition, through the development of UI, it is possible to visualize the operation of the algorithm and effectively communicate the prediction of the model to the user. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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