Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/568614
Title: Dynamic performance improvement of fem optimized ipmsm drive using artificial intelligent based control for ev applications
Researcher: Suganthi,S
Guide(s): Karpagam, R
Keywords: artificial intelligent
Engineering
Engineering and Technology
Engineering Electrical and Electronic
ev applications
University: Anna University
Completed Date: 2024
Abstract: newline Micro Grids have been in focus of recent scientific research as a potential replacement for current energy system outlooks. Micro Grids are being considered as a potential solution for integrating various RES into the standard grid. AC-DC hybrid MG includes DC and AC buses connected with Distributed generators, energy storage systems and load. The presence of several interleaved converters in the microgrid complicates the control operation and generates circulating currents which lowers the available current capacity of the Inter Linking Converters (ILCs). Hence a single ILC topology has been employed as an interface between DC and AC subgrids, which is the most attractive solution for a paradigm of future smart grids. It is also essential to optimize the control parameters of the controller in order to improve the reliability of the system. An effort has been made in the present research work to optimize AC-DC hybrid MG using two methods and compared with various algorithms.
Pagination: 3,1p.
URI: http://hdl.handle.net/10603/568614
Appears in Departments:Faculty of Electrical Engineering

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01_title.pdfAttached File24.42 kBAdobe PDFView/Open
02_prelim_pages.pdf1.38 MBAdobe PDFView/Open
03_content.pdf12.92 kBAdobe PDFView/Open
04_abstract.pdf7.53 kBAdobe PDFView/Open
05_chapter1.pdf816.32 kBAdobe PDFView/Open
06_chapter2.pdf168.28 kBAdobe PDFView/Open
07_chapter3.pdf940.34 kBAdobe PDFView/Open
08_chapter4.pdf752.9 kBAdobe PDFView/Open
09_chapter5.pdf1.25 MBAdobe PDFView/Open
10_chapter6.pdf43.47 kBAdobe PDFView/Open
11_annexures.pdf158.31 kBAdobe PDFView/Open
80_recommendation.pdf65.77 kBAdobe PDFView/Open
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