K-means and fuzzy relational eigenvector centrality-based clustering algorithms for defensive islanding

Mohammed Mahdi; V. M.Istemihan Genc

doi:10.1109/ISGTEurope.2016.7856210

K-means and fuzzy relational eigenvector centrality-based clustering algorithms for defensive islanding

Mohammed Mahdi
, V. M.Istemihan Genc

Elektrik Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

3 Atıf (Scopus)

Özet

Among the power system corrective controls, defensive islanding is considered as the last resort to secure the system from severe cascading contingencies. The primary motive of defensive islanding is to limit the affected areas to maintain the stability of the resulting subsystems and to reduce the total loss of load in the system. The slow coherency based islanding can successfully be applied for the defensive islanding. In this paper, two partitioning methods are proposed, K-means clustering algorithm and fuzzy relational eigenvector centrality-based clustering algorithm. The proposed methods are using the data measured by phasor measurement units to determine the islands to be used in the defensive islanding. The proposed methods are demonstrated on the 16-generator 68-bus power system and their performances are discussed as their results are compared.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	ISGT Europe 2016 - IEEE PES Innovative Smart Grid Technologies, Europe
Yayınlayan	IEEE Computer Society
ISBN (Elektronik)	9781509033584
DOI'lar	https://doi.org/10.1109/ISGTEurope.2016.7856210
Yayın durumu	Yayınlandı - 2 Tem 2016
Etkinlik	2016 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2016 - Ljubljana, Slovenia Süre: 9 Eki 2016 → 12 Eki 2016

Yayın serisi

Adı	IEEE PES Innovative Smart Grid Technologies Conference Europe

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2016 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2016
Ülke/Bölge	Slovenia
Şehir	Ljubljana
Periyot	9/10/16 → 12/10/16

Bibliyografik not

Publisher Copyright:
© 2016 IEEE.

Belgeye Erişim

10.1109/ISGTEurope.2016.7856210

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

@inproceedings{0bfdc89984264a3d81b2afb2f5df6afb,

title = "K-means and fuzzy relational eigenvector centrality-based clustering algorithms for defensive islanding",

abstract = "Among the power system corrective controls, defensive islanding is considered as the last resort to secure the system from severe cascading contingencies. The primary motive of defensive islanding is to limit the affected areas to maintain the stability of the resulting subsystems and to reduce the total loss of load in the system. The slow coherency based islanding can successfully be applied for the defensive islanding. In this paper, two partitioning methods are proposed, K-means clustering algorithm and fuzzy relational eigenvector centrality-based clustering algorithm. The proposed methods are using the data measured by phasor measurement units to determine the islands to be used in the defensive islanding. The proposed methods are demonstrated on the 16-generator 68-bus power system and their performances are discussed as their results are compared.",

keywords = "defensive islanding, FRECCA clustering, k-means clustering, slow coherency",

author = "Mohammed Mahdi and Genc, \{V. M.Istemihan\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2016 ; Conference date: 09-10-2016 Through 12-10-2016",

year = "2016",

month = jul,

day = "2",

doi = "10.1109/ISGTEurope.2016.7856210",

language = "English",

series = "IEEE PES Innovative Smart Grid Technologies Conference Europe",

publisher = "IEEE Computer Society",

booktitle = "ISGT Europe 2016 - IEEE PES Innovative Smart Grid Technologies, Europe",

address = "United States",

}

Mahdi, M & Genc, VMI 2016, K-means and fuzzy relational eigenvector centrality-based clustering algorithms for defensive islanding. in ISGT Europe 2016 - IEEE PES Innovative Smart Grid Technologies, Europe., 7856210, IEEE PES Innovative Smart Grid Technologies Conference Europe, IEEE Computer Society, 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2016, Ljubljana, Slovenia, 9/10/16. https://doi.org/10.1109/ISGTEurope.2016.7856210

K-means and fuzzy relational eigenvector centrality-based clustering algorithms for defensive islanding. / Mahdi, Mohammed; Genc, V. M.Istemihan.
ISGT Europe 2016 - IEEE PES Innovative Smart Grid Technologies, Europe. IEEE Computer Society, 2016. 7856210 (IEEE PES Innovative Smart Grid Technologies Conference Europe).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - K-means and fuzzy relational eigenvector centrality-based clustering algorithms for defensive islanding

AU - Mahdi, Mohammed

AU - Genc, V. M.Istemihan

PY - 2016/7/2

Y1 - 2016/7/2

N2 - Among the power system corrective controls, defensive islanding is considered as the last resort to secure the system from severe cascading contingencies. The primary motive of defensive islanding is to limit the affected areas to maintain the stability of the resulting subsystems and to reduce the total loss of load in the system. The slow coherency based islanding can successfully be applied for the defensive islanding. In this paper, two partitioning methods are proposed, K-means clustering algorithm and fuzzy relational eigenvector centrality-based clustering algorithm. The proposed methods are using the data measured by phasor measurement units to determine the islands to be used in the defensive islanding. The proposed methods are demonstrated on the 16-generator 68-bus power system and their performances are discussed as their results are compared.

AB - Among the power system corrective controls, defensive islanding is considered as the last resort to secure the system from severe cascading contingencies. The primary motive of defensive islanding is to limit the affected areas to maintain the stability of the resulting subsystems and to reduce the total loss of load in the system. The slow coherency based islanding can successfully be applied for the defensive islanding. In this paper, two partitioning methods are proposed, K-means clustering algorithm and fuzzy relational eigenvector centrality-based clustering algorithm. The proposed methods are using the data measured by phasor measurement units to determine the islands to be used in the defensive islanding. The proposed methods are demonstrated on the 16-generator 68-bus power system and their performances are discussed as their results are compared.

KW - defensive islanding

KW - FRECCA clustering

KW - k-means clustering

KW - slow coherency

UR - https://www.scopus.com/pages/publications/85017558386

U2 - 10.1109/ISGTEurope.2016.7856210

DO - 10.1109/ISGTEurope.2016.7856210

M3 - Conference contribution

AN - SCOPUS:85017558386

T3 - IEEE PES Innovative Smart Grid Technologies Conference Europe

BT - ISGT Europe 2016 - IEEE PES Innovative Smart Grid Technologies, Europe

PB - IEEE Computer Society

T2 - 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2016

Y2 - 9 October 2016 through 12 October 2016

ER -

K-means and fuzzy relational eigenvector centrality-based clustering algorithms for defensive islanding

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