Defensive islanding using self-organizing maps neural networks and hierarchical clustering

Mohammed Mahdi; Istemihan Genc

doi:10.1109/PTC.2015.7232427

Defensive islanding using self-organizing maps neural networks and hierarchical clustering

Mohammed Mahdi, Istemihan Genc

Elektrik Mühendisliği Bölümü

Istanbul Technical University

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

11 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 objective is 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 new partitioning methods, hierarchical clustering and clustering using self-organizing maps neural networks, have been proposed to determine the clusters 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	2015 IEEE Eindhoven PowerTech, PowerTech 2015
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9781479976935
DOI'lar	https://doi.org/10.1109/PTC.2015.7232427
Yayın durumu	Yayınlandı - 31 Ağu 2015
Etkinlik	IEEE Eindhoven PowerTech, PowerTech 2015 - Eindhoven, Netherlands Süre: 29 Haz 2015 → 2 Tem 2015

Yayın serisi

Adı	2015 IEEE Eindhoven PowerTech, PowerTech 2015

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

???event.eventtypes.event.conference???	IEEE Eindhoven PowerTech, PowerTech 2015
Ülke/Bölge	Netherlands
Şehir	Eindhoven
Periyot	29/06/15 → 2/07/15

Bibliyografik not

Publisher Copyright:
© 2015 IEEE.

Belgeye Erişim

10.1109/PTC.2015.7232427

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

@inproceedings{10b8e6483e634cfbb5b5eec78d0b562f,

title = "Defensive islanding using self-organizing maps neural networks and hierarchical clustering",

abstract = "Among the power system corrective controls, defensive islanding is considered as the last resort to secure the system from severe cascading contingencies. The objective is 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 new partitioning methods, hierarchical clustering and clustering using self-organizing maps neural networks, have been proposed to determine the clusters 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, hierarchical clustering, self-organizing maps neural networks, slow coherency",

author = "Mohammed Mahdi and Istemihan Genc",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE Eindhoven PowerTech, PowerTech 2015 ; Conference date: 29-06-2015 Through 02-07-2015",

year = "2015",

month = aug,

day = "31",

doi = "10.1109/PTC.2015.7232427",

language = "English",

series = "2015 IEEE Eindhoven PowerTech, PowerTech 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2015 IEEE Eindhoven PowerTech, PowerTech 2015",

address = "United States",

}

Mahdi, M & Genc, I 2015, Defensive islanding using self-organizing maps neural networks and hierarchical clustering. in 2015 IEEE Eindhoven PowerTech, PowerTech 2015., 7232427, 2015 IEEE Eindhoven PowerTech, PowerTech 2015, Institute of Electrical and Electronics Engineers Inc., IEEE Eindhoven PowerTech, PowerTech 2015, Eindhoven, Netherlands, 29/06/15. https://doi.org/10.1109/PTC.2015.7232427

Defensive islanding using self-organizing maps neural networks and hierarchical clustering. / Mahdi, Mohammed; Genc, Istemihan.
2015 IEEE Eindhoven PowerTech, PowerTech 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7232427 (2015 IEEE Eindhoven PowerTech, PowerTech 2015).

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

TY - GEN

T1 - Defensive islanding using self-organizing maps neural networks and hierarchical clustering

AU - Mahdi, Mohammed

AU - Genc, Istemihan

PY - 2015/8/31

Y1 - 2015/8/31

N2 - Among the power system corrective controls, defensive islanding is considered as the last resort to secure the system from severe cascading contingencies. The objective is 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 new partitioning methods, hierarchical clustering and clustering using self-organizing maps neural networks, have been proposed to determine the clusters 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 objective is 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 new partitioning methods, hierarchical clustering and clustering using self-organizing maps neural networks, have been proposed to determine the clusters 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 - hierarchical clustering

KW - self-organizing maps neural networks

KW - slow coherency

UR - http://www.scopus.com/inward/record.url?scp=84951311117&partnerID=8YFLogxK

U2 - 10.1109/PTC.2015.7232427

DO - 10.1109/PTC.2015.7232427

M3 - Conference contribution

AN - SCOPUS:84951311117

T3 - 2015 IEEE Eindhoven PowerTech, PowerTech 2015

BT - 2015 IEEE Eindhoven PowerTech, PowerTech 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE Eindhoven PowerTech, PowerTech 2015

Y2 - 29 June 2015 through 2 July 2015

ER -

Defensive islanding using self-organizing maps neural networks and hierarchical clustering

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Bibliyografik not

Belgeye Erişim

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