Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/586079
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dc.coverage.spatialSolar PV System
dc.date.accessioned2024-08-29T06:24:38Z-
dc.date.available2024-08-29T06:24:38Z-
dc.identifier.urihttp://hdl.handle.net/10603/586079-
dc.description.abstractIn the realm of renewable energy systems, the extraction of maximum available newlinepower from photovoltaic (PV) panels has become a paramount objective to enhance newlineoverall system efficiency and viability. This thesis delves into the development, analysis, newlineand optimization of a Maximum Power Point Tracking (MPPT) controller for PV newlinesystems. The MPPT controller s primary objective is to dynamically adjust the load newlineimpedance to maintain the solar panel operating point at its maximum power output, newlinethereby ensuring efficient energy conversion. newlineThe thesis commences with a comprehensive survey of existing MPPT techniques, newlineencompassing Perturb and Observe (PandO), Incremental Conductance (IncCond), and newlinevarious model-based algorithms. This analysis provides valuable insights into the newlinestrengths and limitations of each technique, forming the foundation for the subsequent newlineresearch. newlineCentral to the thesis is the design and implementation of an advanced MPPT controller newlineleveraging fuzzy logic techniques Fuzzy logic offers the ability to capture the newlineinherent uncertainties and nonlinearities of the PV system while delivering adaptive newlineand robust control. The proposed controller is compared against conventional newlinemethods through extensive simulations and experimental validations. The results newlinedemonstrate the superiority of the fuzzy logic-based MPPT controller, exhibiting enhanced newlinetracking accuracy, rapid convergence, and resilience to changing atmospheric newlineconditions. newlineFurthermore, the thesis explores the integration of Particle Swarm optimization newlinetechniques, basic techniques, into the MPPT control framework. This hybrid approach newlinecombines the adaptability of Particle Swarm optimization with the datadriven newlinecapabilities. Training and optimization procedures are detailed, showcasing newlinethe potential for improved performance and adaptability under varying operating newlineconditions. newlineThe study concludes with a comprehensive analysis of the proposed MPPT controller s newlineapplicability across diverse PV system configurations, environmental condiiv newlinetions, and load p
dc.format.extent173p
dc.languageEnglish
dc.relation177b
dc.rightsuniversity
dc.titleInvestigation of the Tracking and Quality of Power in the Solar PV System
dc.title.alternative
dc.creator.researcherRajbhoj, Pankaj Rajendra
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordInstruments and Instrumentation
dc.description.note
dc.contributor.guideHamde, Satish T.
dc.publisher.placeNanded
dc.publisher.universitySwami Ramanand Teerth Marathwada University
dc.publisher.institutionDepartment of Instrumentation Engineering
dc.date.registered2017
dc.date.completed2024
dc.date.awarded2024
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Instrumentation Engineering

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01_title.pdfAttached File61.86 kBAdobe PDFView/Open
02_prelim pages.pdf103.46 kBAdobe PDFView/Open
03_contents.pdf46.88 kBAdobe PDFView/Open
04_abstract.pdf46.18 kBAdobe PDFView/Open
05_chapter 1.pdf97.67 kBAdobe PDFView/Open
06_chapter 2.pdf1.39 MBAdobe PDFView/Open
07_chapter 3.pdf1.8 MBAdobe PDFView/Open
08_chapter 4.pdf461.85 kBAdobe PDFView/Open
09_chapter 5.pdf414.83 kBAdobe PDFView/Open
10_chapter 6.pdf863.87 kBAdobe PDFView/Open
11_annexures.pdf109.56 kBAdobe PDFView/Open
80_recommendation.pdf105.13 kBAdobe PDFView/Open


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