Application of machine learning on power system dynamic security assessment

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	2014-03-01T02:44:28Z
dc.date.available	2014-03-01T02:44:28Z
dc.date.issued	2007	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31837
dc.subject	Decision trees	en
dc.subject	Dynamic security assessment	en
dc.subject	Machine learning neural networks	en
dc.subject	Probabilistic neural networks	en
dc.subject	Radial basis function neural networks	en
dc.subject	Self organizing maps	en
dc.subject	Support vector machines	en
dc.subject.other	Dynamic security assessment	en
dc.subject.other	International conferences	en
dc.subject.other	Machine learning neural networks	en
dc.subject.other	Machine-learning	en
dc.subject.other	Operating points	en
dc.subject.other	Paper addresses	en
dc.subject.other	Power systems	en
dc.subject.other	Probabilistic neural networks	en
dc.subject.other	Radial basis function neural networks	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Decision making	en
dc.subject.other	Decision theory	en
dc.subject.other	Decision trees	en
dc.subject.other	Education	en
dc.subject.other	Electric power systems	en
dc.subject.other	Electric power transmission networks	en
dc.subject.other	Feedforward neural networks	en
dc.subject.other	Intelligent systems	en
dc.subject.other	Learning systems	en
dc.subject.other	Maps	en
dc.subject.other	Nuclear materials safeguards	en
dc.subject.other	Power transmission	en
dc.subject.other	Radial basis function networks	en
dc.subject.other	Robot learning	en
dc.subject.other	Self organizing maps	en
dc.subject.other	Supervised learning	en
dc.subject.other	Support vector machines	en
dc.subject.other	Neural networks	en
dc.title	Application of machine learning on power system dynamic security assessment	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ISAP.2007.4441604	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ISAP.2007.4441604	en
heal.identifier.secondary	4441604	en
heal.publicationDate	2007	en
heal.abstract	This paper addresses the on going work of the application of Machine Learning on Dynamic Security Assessment of Power Systems. Several techniques, which have been applied for the Dynamic Security Assessment of the Greek Power System are presented. These techniques include off-line Supervised learning (Radial Basis Function Neural Networks, Support Vector Machines, Decision Trees), off-line Unsupervised learning (Self Organizing Maps) and online Supervised learning (Probabilistic Neural Networks). Results from the application of these methods on operating point series from the Greek Mainland system and the Power System of Crete island show the accuracy and versatility of the methods.	en
heal.journalName	2007 International Conference on Intelligent Systems Applications to Power Systems, ISAP	en
dc.identifier.doi	10.1109/ISAP.2007.4441604	en