Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/301642
Title: Mppt controlled qzsi based pv and wind energy conversion system
Researcher: Sathishkumar R
Guide(s): V. Malathi
Keywords: Wind energy
Renewable Energy Sources
Artificial Neural Network
University: Anna University
Completed Date: 2019
Abstract: For the enormously increased power demand in the modern world the existing fossil fuel sources seem to be inadequate to meet the demands Hence it is necessary to switch over to use Renewable Energy Sources RES Besides the demand concerns the power generation from fossil fuels causes the environmental pollution prominently As a result the utilization of RES has been encouraged When RES is interconnected with the grid this system becomes an excellent solution to fulfill the power demand of present scenario The energy generated from the renewable energy sources vary according to the seasonal variations The power generated from RES can be delivered to the load by interconnecting it with the grid When a small size RES system is connected with the distribution network it can deliver energy to the isolated zones where the energy cannot be drawn from the conventional network A dual configuration for integrating the wind and the solar with the grid has been proposed in this thesis based on the single and the dual stages In the first work the Quasi Z Source Inverter qZSI based Photo Voltaic PV source integration with the grid is carried out In order to extract maximum power from PV an Artificial Neural Network ANN based Maximum Power Point Tracking MPPT scheme has been introduced in this work Also a bi directional charger is introduced to overcome the battery issues The model is simulated in MATLAB SIMULINK software The performance of the system is analysed by applying different voltage levels to qZSI The voltage gain efficiency of system MPP tracking and the regulation of the voltages are observed newline
Pagination: xxi,160p.
URI: http://hdl.handle.net/10603/301642
Appears in Departments:Faculty of Electrical Engineering

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05_contents.pdf.pdf32.21 kBAdobe PDFView/Open
06_list_of_tables.pdf.pdf5.48 kBAdobe PDFView/Open
07_list_of_figures.pdf25.17 kBAdobe PDFView/Open
08_list_of_abbreviations.pdf11.44 kBAdobe PDFView/Open
09_chapter1.pdf.pdf307.58 kBAdobe PDFView/Open
10_chapter2.pdf.pdf1.18 MBAdobe PDFView/Open
11_chapter3.pdf.pdf1.13 MBAdobe PDFView/Open
12_chapter4.pdf.pdf1.42 MBAdobe PDFView/Open
13_chapter5.pdf.pdf1.03 MBAdobe PDFView/Open
14_conclusion.pdf.pdf91.42 kBAdobe PDFView/Open
15_references.pdf.pdf128.08 kBAdobe PDFView/Open
16_list_of_publications.pdf67.8 kBAdobe PDFView/Open
80_recommendation.pdf148.9 kBAdobe PDFView/Open
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