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Title: Selective elimination of harmonics in ups inverters using hybrid techniques
Researcher: Merry Geisa J
Guide(s): Rajaram M
Keywords: Harmonics
Total harmonic distortion
Uninterruptible Power Supply
Upload Date: 27-Feb-2014
University: Anna University
Completed Date: 01/11/2013
Abstract: In today s commercial world, Uninterruptible Power Supply (UPS) is playing a significant role in preventing the computer from power failure. Inverter is one of the essential components of UPS that performs DC-AC conversion. In this process, there is a possibility of generation of harmonic peaks because majority of the power utilities are nonlinear loads.A high performance UPS system should have a clean output voltage with low total harmonic distortion (THD) for both linear and nonlinear loads, high efficiency, great reliability and fast transient response for sudden power grid failure and load changes.Irrespective of variations in the input source or load condition, maintaining a constant voltage and constant frequency supply for critical loads, is the major function of an UPS. Due to the rapid rate of increasing loads and the comprehensive use of nonlinear loads in power systems, power quality has become a very important topic especially after power system restructuring. Harmonic distortion is the most important power quality problem occurring in UPS. In UPS powered by a multilevel inverter, the harmonics can be eliminated by an optimal selection of switching angles. Initially, fuzzy logic and neural network controllers have been designed for selectively eliminate the harmonics in multilevel inverters. Mamdani type of inference system is used for the fuzzy logic controller for switching angle selection and the optimal switching angles are used to reduce the Total Harmonic Distortion. A novel concept of application of Artificial Neural Networks (ANN) for estimating the optimum switching angles for cascaded multilevel inverters is also presented. In this paper, the ANN is trained off-line using the desired switching angles. After training the proposed ANN system, a large and memory-demanding look-up table is replaced with trained neural network to generate the optimum switching angles with lowest THD.
Pagination: xix, 178p.
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File87.26 kBAdobe PDFView/Open
02_certificates.pdf2.38 MBAdobe PDFView/Open
03_abstracts.pdf9.22 kBAdobe PDFView/Open
04_acknowledgement.pdf5.9 kBAdobe PDFView/Open
05_contents.pdf26.41 kBAdobe PDFView/Open
06_chapter 1.pdf163.24 kBAdobe PDFView/Open
07_chapter 2.pdf49.76 kBAdobe PDFView/Open
08_chapter 3.pdf546.11 kBAdobe PDFView/Open
09_chapter 4.pdf388.65 kBAdobe PDFView/Open
10_chapter 5.pdf930.32 kBAdobe PDFView/Open
11_chapter 6.pdf335.69 kBAdobe PDFView/Open
12_chapter 7.pdf13.01 kBAdobe PDFView/Open
13_appendix.pdf36.78 kBAdobe PDFView/Open
14_references.pdf34.22 kBAdobe PDFView/Open
15_publications.pdf5.73 kBAdobe PDFView/Open
16_vitae.pdf5.93 kBAdobe PDFView/Open

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