Zobrazeno 1 - 10 of 89 pro vyhledávání: '"June-Ho Park"'
1
Akademický článek
Transient Stability Assessment Using Deep Transfer Learning
Autor: Jongju Kim, Heungseok Lee, Sungshin Kim, Sang-Hwa Chung, June Ho Park
Publikováno v: IEEE Access, Vol 11, Pp 116622-116637 (2023)
This study proposes a deep transfer learning method using a deep convolutional neural network pre-trained with ImageNet for transient stability assessment. The procedure of deep transfer learning, incorporating the role and considerations of the tran
Externí odkaz: https://doaj.org/article/bf7c832d7ca24475b934a3562d19fb08
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2
Akademický článek
Power System Transient Stability Assessment Using Convolutional Neural Network and Saliency Map
Autor: Heungseok Lee, Jongju Kim, June Ho Park, Sang-Hwa Chung
Publikováno v: Energies, Vol 16, Iss 23, p 7743 (2023)
This study proposes a model for transient stability assessment, which is a convolutional neural network model combined with a saliency map (S–CNN model). The convolutional neural network model is trained on dynamic data acquired through the data me
Externí odkaz: https://doaj.org/article/8c0f981220024088b4f2edc2d0f0de31
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4
Akademický článek
A Novel Structure of a Power System Stabilizer for Microgrids
Autor: Jong Ju Kim, June Ho Park
Publikováno v: Energies, Vol 14, Iss 4, p 905 (2021)
This paper proposes a novel structure of a power system stabilizer (PSS) to improve the stability of synchronous generators (SGs) in microgrids. Microgrids are relatively vulnerable in terms of stability due to their small size and low inertia. The r
Externí odkaz: https://doaj.org/article/5418e35fc6164021aa7f332dfe9add09
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8
A Study on Wind Power Forecasting Using LSTM Method
Autor: Heungseok Lee, Kyuhan Kim, Hyung-Su Kim, Hwa-Seok Lee, June Ho Park, Hee-Myung Jeong
Publikováno v: The transactions of The Korean Institute of Electrical Engineers. 69:1157-1164
Recently, as the need for renewable and alternative energy increases, the proportion of wind power generation is increasing. The wind power generation can be produced anywhere in the windy place through fixed function. Commonly, the wind power genera
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::af8ea216d3221a6c47ad6494a916f435
https://doi.org/10.5370/kiee.2020.69.8.1157
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10
Akademický článek
A New Input Selection Algorithm Using the Group Method of Data Handling and Bootstrap Method for Support Vector Regression Based Hourly Load Forecasting
Autor: Jungwon Yu, June Ho Park, Sungshin Kim
Publikováno v: Energies, Vol 11, Iss 11, p 2870 (2018)
Electric load forecasting is indispensable for the effective planning and operation of power systems. Various decisions related to power systems depend on the future behavior of loads. In this paper, we propose a new input selection procedure, which
Externí odkaz: https://doaj.org/article/253e2cb1b6c9415ca2f9f06d9379e5c5
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