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Decision trees-aided self-organized maps for corrective dynamic security

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dc.contributor.author Voumvoulakis, EM en
dc.contributor.author Hatziargyriou, ND en
dc.date.accessioned 2014-03-01T01:28:07Z
dc.date.available 2014-03-01T01:28:07Z
dc.date.issued 2008 en
dc.identifier.issn 0885-8950 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/18710
dc.subject Artificial intelligence en
dc.subject Corrective control en
dc.subject Decision trees en
dc.subject Dynamic security en
dc.subject Load shedding en
dc.subject Machine learning en
dc.subject Preventive control en
dc.subject Self-organized maps en
dc.subject.classification Engineering, Electrical & Electronic en
dc.subject.other Artificial intelligence en
dc.subject.other Decision trees en
dc.subject.other Learning systems en
dc.subject.other Self organizing maps en
dc.subject.other Corrective control en
dc.subject.other Dynamic security en
dc.subject.other Hellenic power system en
dc.subject.other Electric load shedding en
dc.title Decision trees-aided self-organized maps for corrective dynamic security en
heal.type journalArticle en
heal.identifier.primary 10.1109/TPWRS.2008.920194 en
heal.identifier.secondary http://dx.doi.org/10.1109/TPWRS.2008.920194 en
heal.language English en
heal.publicationDate 2008 en
heal.abstract Difficulties in expanding the generation and transmission system force modern power systems to operate often close to their stability limits, in order to meet the continuously growing demand. An effective way to face power system contingencies that can lead to instability is load shedding. This paper proposes a machine learning framework for the evaluation of load shedding for corrective dynamic security of the system. The proposed method employs a self-organized map with decision trees nested in some of its nodes in order to classify the load profiles of a power system. The method is applied on a realistic model of the Hellenic Power System and its added value is shown by comparing results with the ones obtained from the application of simple self-organized maps and simple decision trees. © 2008 IEEE. en
heal.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC en
heal.journalName IEEE Transactions on Power Systems en
dc.identifier.doi 10.1109/TPWRS.2008.920194 en
dc.identifier.isi ISI:000258765900040 en
dc.identifier.volume 23 en
dc.identifier.issue 2 en
dc.identifier.spage 622 en
dc.identifier.epage 630 en


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