Decision trees for dynamic security assessment and load shedding scheme

Voumvoulakis, EM; Gavoyiannis, AE; Hatziargyriou, ND

dc.contributor.author	Voumvoulakis, EM	en
dc.contributor.author	Gavoyiannis, AE	en
dc.contributor.author	Hatziargyriou, ND	en
dc.date.accessioned	2014-03-01T02:43:59Z
dc.date.available	2014-03-01T02:43:59Z
dc.date.issued	2006	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31600
dc.subject	Data mining	en
dc.subject	Decision trees	en
dc.subject	Dynamic security assessment	en
dc.subject	Load shedding	en
dc.subject.other	Data mining	en
dc.subject.other	Decision trees	en
dc.subject.other	Electric load loss	en
dc.subject.other	Electric power generation	en
dc.subject.other	Frequency stability	en
dc.subject.other	Critical contingencies	en
dc.subject.other	Dynamic security assessment	en
dc.subject.other	Greek mainland Power Systems	en
dc.subject.other	Load shedding	en
dc.subject.other	Electric power system protection	en
dc.title	Decision trees for dynamic security assessment and load shedding scheme	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/PES.2006.1709418	en
heal.identifier.secondary	http://dx.doi.org/10.1109/PES.2006.1709418	en
heal.identifier.secondary	1709418	en
heal.publicationDate	2006	en
heal.abstract	Modern Power Systems often operate close to their stability limits in order to meet the continuously growing demand, due to the difficulties in expanding the generation and transmission system. An effective way to face power system contingencies that can lead to instability is load shedding. In this paper we propose a method to assess the dynamic performance of the Greek mainland Power System and to propose a load shedding scheme in order to maintain voltage stability under various loading conditions and operating states in the presence of critical contingencies including outages of one or more generating units in the south part of the system. A Decision Tree is used to assess the dynamic Performance of the system. The candidate attributes of the Decision Tree are chosen through a data mining process. © 2006 IEEE.	en
heal.journalName	2006 IEEE Power Engineering Society General Meeting, PES	en
dc.identifier.doi	10.1109/PES.2006.1709418	en