A Fast Screening Method for Transient Stability considering Multi-swing Step-out using Pattern Recognition with Machine Learning and Clustering
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- Kobayashi Junnosuke
- Dept. of Electrical Eng. & Bioscience, Waseda University
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- Koyanagi Yui
- Dept. of Electrical Eng. & Bioscience, Waseda University
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- Iwamoto Shinichi
- Dept. of Electrical Eng. & Bioscience, Waseda University
Bibliographic Information
- Other Title
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- 機械学習を用いたパターン認識とクラスタリングによるN波脱調を考慮した過渡安定度高速安定判別手法
- キカイ ガクシュウ オ モチイタ パターン ニンシキ ト クラスタリング ニ ヨル Nハ ダツチョウ オ コウリョ シタ カト アンテイド コウソク アンテイ ハンベツ シュホウ
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Abstract
<p>Recently, online stability monitoring systems have become more important in response to the increasing complexity of power systems. Moreover, there has been a concern about multi-swing step-out due to the Japanese longitudinal power system. In this paper, a fast screening method is proposed considering multi-swing step-out using PCA (principal component analysis). In the proposed method, computers learn patterns of PCA in transient stability data as a form of library. In order to reduce the number of data in the library, k-means method, one of the partitioning-optimization clustering methods, is applied to extract features in the data. In addition, Gaussian mixture model is also applied to extract the feature from a different perspective. Simulations for the proposed method are performed using the IEEJ 10 machine 47 bus system to confirm the validity of the screening method.</p>
Journal
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- IEEJ Transactions on Power and Energy
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IEEJ Transactions on Power and Energy 137 (8), 559-565, 2017
The Institute of Electrical Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390001204606062720
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- NII Article ID
- 130005876212
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- NII Book ID
- AN10136334
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- ISSN
- 13488147
- 03854213
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- NDL BIB ID
- 028463916
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed