Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/38611
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dc.coverage.spatialInvestigations on application of Various evolutionary programming Techniques for optimal power flow Problem including facts and dg devicesen_US
dc.date.accessioned2015-04-06T04:35:02Z-
dc.date.available2015-04-06T04:35:02Z-
dc.date.issued2015-04-06-
dc.identifier.urihttp://hdl.handle.net/10603/38611-
dc.description.abstractnewlineThe Optimal Power Flow OPF problem is a non linear newlineprogramming and highly constrained optimization problem The goal of OPF newlineis to find the optimal settings of a given power system network that optimizes newlinethe systems objective functions such as total generation cost system loss bus newlinevoltage deviation while satisfying its power flow equations system security newlineand equipment operating limits newlineWith the evolution of Flexible AC Transmission FACTS devices newlineit is made easy to control the power flow in a bus system FACTS devices newlinesuch as Thyristor Controlled Series Compensator TCSC Static VAr newlineCompensators SVC provides flexibility in control of real power and reactive newlinepower in transmission line The use of the FACTS device allows the newlinetransmission line to increase the voltage and stability limits newlineThis research work solves the Optimal Power Flow for fuel cost newlineminimization with the power flow constraints through effective application of newlineGravitational Search Algorithm GSA for OPF problem and optimal type newlinesizing and allocation of FACTS devices using Genetic Algorithm GA newlineconsidering the power flow equations as the equality constraints limits on the newlineactive and reactive power generations of the units and voltage magnitude newline newlineen_US
dc.format.extentxxv, 166p.en_US
dc.languageEnglishen_US
dc.relationp154-164.en_US
dc.rightsuniversityen_US
dc.titleInvestigations on application of Various evolutionary programming Techniques for optimal power flow Problem including facts and dg devicesen_US
dc.title.alternativeen_US
dc.creator.researcherBelwin edward Jen_US
dc.subject.keywordFlexible AC Transmissionen_US
dc.subject.keywordGenetic Algorithmen_US
dc.subject.keywordGravitational Search Algorithmen_US
dc.subject.keywordOptimal Power Flowen_US
dc.subject.keywordStatic VAr Compensatorsen_US
dc.subject.keywordThyristor Controlled Series Compensatoren_US
dc.description.noteappendix p147-153, reference p154-164.en_US
dc.contributor.guideRajaram Men_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Electrical and Electronics Engineeringen_US
dc.date.registeredn.d,en_US
dc.date.completed01/01/2014en_US
dc.date.awarded30/01/2014en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File28.67 kBAdobe PDFView/Open
02_certificate.pdf936.28 kBAdobe PDFView/Open
03_abstract.pdf9.84 kBAdobe PDFView/Open
04_acknowledgement.pdf5.59 kBAdobe PDFView/Open
05_content.pdf89.45 kBAdobe PDFView/Open
06_chapter1.pdf159.38 kBAdobe PDFView/Open
07_chapter2.pdf185.55 kBAdobe PDFView/Open
08_chapter3.pdf366.86 kBAdobe PDFView/Open
10_chapter5.pdf742.78 kBAdobe PDFView/Open
11_chapter6.pdf775.73 kBAdobe PDFView/Open
12_chapter7.pdf137.63 kBAdobe PDFView/Open
13_appendix.pdf301.76 kBAdobe PDFView/Open
14_reference.pdf602.28 kBAdobe PDFView/Open
15_publication.pdf36.92 kBAdobe PDFView/Open


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