Development of Automatic Voltage Stabilization System for Substation Using Deep Learning
- Authors
- Moon, Jiyong; Son, Minyeong; Oh, Byeongchan; Jin, Jeongpil; Kim, Kwangil; Shin, 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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- Appears in
Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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