Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/8602
Full metadata record
DC FieldValueLanguage
dc.contributor.authorChavda, Pratiksinh Bhupendrasinh-
dc.date.accessioned2019-08-03T06:41:17Z-
dc.date.available2019-08-03T06:41:17Z-
dc.date.issued2017-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/8602-
dc.description.abstractIn order to meet the increasing demand of electric power, it is necessary operate multiple generators in parallel to each other. The instant of synchronization plays vital role in the purview of system stability and mechanical forces subjected on the shaft of the machine and hence there is requirement of predicting the proper instant of synchronization. If two alternators are not synchronized properly, there will be synchronizing current owing between two alternators. When all necessary and essential conditions are matched, synchronizing current would be zero, else it will have some magnitude corresponding to mismatch of parameters i.e. voltage, frequency etc. Based on this idea, using this synchronous current signal for different conditions a control strategy has to be developed to determine correct instant for smooth synchronization of alternator. Synchronizing current is the ratio of difference between phase voltages of two alternators and synchronous impedance. To determine synchronous impedance there is a requirement to obtain synchronous reactance first but it will change with change in load and power factor due to this synchronous impedance is changing. so, there will be needed to obtain optimum value of synchronous impedance to calculate synchronizing current. To determine synchronous reactance AI technique is more suitable. So that one possibility of synchronous impedance estimation via Genetic Algorithm has been presented here. The results obtained using AI technique is validated using conventional experimental method.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries15MEEE04;-
dc.subjectElectrical 2015en_US
dc.subjectProject Report 2015en_US
dc.subjectElectrical Project Reporten_US
dc.subjectProject Reporten_US
dc.subject15MEEen_US
dc.subject15MEEEen_US
dc.subject15MEEE04en_US
dc.subjectEPSen_US
dc.subjectEPS 2015en_US
dc.subjectEE (EPS)en_US
dc.subjectElectrical Power Systemsen_US
dc.titleEstimation of Optimal Value of Synchronous Impedance using Artificial Intelligence Techniqueen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, EE (EPS)

Files in This Item:
File Description SizeFormat 
15MEEE04.pdf15MEEE044.09 MBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.