書誌事項
- タイトル別名
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- A Fast Screening Method for Transient Stability considering Multi-swing Step-out using Pattern Recognition with Machine Learning and Clustering
- 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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説明
<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>
収録刊行物
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- 電気学会論文誌B(電力・エネルギー部門誌)
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電気学会論文誌B(電力・エネルギー部門誌) 137 (8), 559-565, 2017
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390001204606062720
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- NII論文ID
- 130005876212
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- NII書誌ID
- AN10136334
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- ISSN
- 13488147
- 03854213
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- NDL書誌ID
- 028463916
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可