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dc.contributor.authorKumar, D.M.V.-
dc.contributor.authorReddy, G.N.-
dc.contributor.authorVenkaiah, Ch.-
dc.date.accessioned2024-12-03T10:08:52Z-
dc.date.available2024-12-03T10:08:52Z-
dc.date.issued2006-05-
dc.identifier.citation10.1109/POWERI.2006.1632590en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1931-
dc.descriptionNITWen_US
dc.description.abstractn this paper ATC has been computed for real time applications using three different intelligent techniques viz., i) back propagation algorithm (BPA) ii) radial basis function (RBF) neural network and iii) adaptive neuro fuzzy inference system (ANFIS). The ATC is to be made available on open access same time information system (OASIS), which is accessible to seller and buyer. The independent system operator (ISO) updates the ATC in real time. The three different methods are tested on IEEE 24-bus reliability test system (RTS) and compared with the conventional full AC load flow method for the base case, different transactions and line outage casesen_US
dc.language.isoenen_US
dc.publisherPower India Conference, 2006 IEEEen_US
dc.subjectIntelligent Techniquesen_US
dc.subjectATCen_US
dc.subjectPower System Deregulationen_US
dc.subjectReal-Time Applicationsen_US
dc.titleAvailable Transfer Capability (ATC) determination using intelligent techniquesen_US
dc.typeOtheren_US
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