Multicontingency Steady-State Security Evaluation Using Fuzzy Clustering Techniques

Matos, M; Hatziargyriou, N; Pecas Lopes, J

dc.contributor.author	Matos, M	en
dc.contributor.author	Hatziargyriou, N	en
dc.contributor.author	Pecas Lopes, J	en
dc.date.accessioned	2014-03-01T01:48:40Z
dc.date.available	2014-03-01T01:48:40Z
dc.date.issued	1999	en
dc.identifier.issn	02721724	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25544
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-33747347589&partnerID=40&md5=66cb176d79651a2950fc6a02e74cb00e	en
dc.subject	Contingencies	en
dc.subject	EMS	en
dc.subject	Fuzzy classifiers	en
dc.subject	Online evaluation	en
dc.subject	Steady-state security assessment	en
dc.title	Multicontingency Steady-State Security Evaluation Using Fuzzy Clustering Techniques	en
heal.type	journalArticle	en
heal.publicationDate	1999	en
heal.abstract	This paper provides a description of a new approach for steady-state security evaluation, using fuzzy nearest prototype classifiers. The basic method has an offline training phase, used to design the fast classifiers for online purposes, allowing more than the two traditional security classes. A battery of these fuzzy classifiers, valid for a specific configuration of the network, is adopted to produce a global evaluation for all relevant single contingencies. An important feature of this approach is that it selects automatically the most appropriate number of security clusters for each selected contingency. Natural language labeling is also used to produce standardized sentences about the security level of the system, improving in this way the communication process between the system and the operator. The paper is completed by an example on a realistic model of the Hellenic Interconnected power system, where seven contingencies were simulated.	en
heal.journalName	IEEE Power Engineering Review	en
dc.identifier.volume	19	en
dc.identifier.issue	3	en
dc.identifier.spage	54	en