Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/224894
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dc.coverage.spatialSmart grid based residential energy Management using soft computing Techniques
dc.date.accessioned2018-12-31T10:20:56Z-
dc.date.available2018-12-31T10:20:56Z-
dc.identifier.urihttp://hdl.handle.net/10603/224894-
dc.description.abstractElectricity is mainly consumed by industrial commercial and residential newlinesectors from which the residential sector is expected to play a vital role in the newlineemerging smart grid framework Residential electricity demand is highly newlinevolatile in nature and is one of the key contributors of any countrys energy newlinepolicy It is therefore critical to understand the current status and future newlinescenarios of demand for electricity at household level for optimal electricity newlinegeneration infrastructure planning and pricing policyElectricity demand studies have been used for numerous reasons over the newlinepast four decades Understanding of the energy demand pattern helps the newlineutilities to adjust generation levels as per the actual demands estimated newlineResidential sector is expected to play a key role in smart grid framework as it is newlinecurrently one of the main contributors of any countrys energy balance newlineEuropean Commission EU Energy in Figures, Statistical Pocketbook newlineEuropean Commission Brussels Belgium 2012 newline newline
dc.format.extentxviii, 122p.
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleSmart grid based residential energy Management using soft computing Techniques
dc.title.alternative
dc.creator.researcherAmutha venkatessh
dc.subject.keywordenergy Management
dc.subject.keywordEngineering and Technology,Computer Science,Computer Science Software Engineering
dc.subject.keywordSmart grid
dc.description.notep. 111-121.
dc.contributor.guideJayashree L S
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registeredn.d.
dc.date.completed01/03/2018
dc.date.awarded30/03/2018
dc.format.dimensions23cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File44.73 kBAdobe PDFView/Open
02_certificate.pdf46.86 kBAdobe PDFView/Open
03_abstract.pdf70.9 kBAdobe PDFView/Open
04_acknowledgement.pdf9.08 kBAdobe PDFView/Open
05_contents.pdf108.08 kBAdobe PDFView/Open
06_chapter 1.pdf267.08 kBAdobe PDFView/Open
07_chapter 2.pdf113.5 kBAdobe PDFView/Open
08_chapter 3.pdf356.28 kBAdobe PDFView/Open
09_chapter 4.pdf515.69 kBAdobe PDFView/Open
10_chapter 5.pdf176.61 kBAdobe PDFView/Open
11_chapter 6.pdf39.12 kBAdobe PDFView/Open
12_references.pdf80.75 kBAdobe PDFView/Open
13_publications.pdf71.02 kBAdobe PDFView/Open


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