Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/301721
Title: | Performance analysis of PV based dynamic voltage restorer for power quality improvement using artificial intelligent techniques |
Researcher: | Santhana Lakshmi C |
Guide(s): | Nagarajan C |
Keywords: | Dynamic voltage Particle swarm optimization Artificial intelligent |
University: | Anna University |
Completed Date: | 2019 |
Abstract: | Recently researches in the area of power quality issues are increasing due to the increased use of sensitive loads on the distribution side If this issue is not addressed properly then it will severely affects the end users who avails this power Thus the major power quality issues faced in distribution network are voltage sag swell harmonic distortion and imbalance in phases This is mainly due to the presence of non linear loads These power quality issues necessitate the development of efficient power quality conditioner to compensate its effects Hence Dynamic Voltage Restorer DVR is designed and effected for power quality improvement in terms of harmonics and voltage sag compensation Hence the main objective of this work is to design an optimized DVR to overcome the power quality issue addressed in the distribution system In this proposed work the PV module with Perturbation and Observation P O algorithm based Maximum Power Point Tracking MPPT and Particle Swarm Optimization PSO based MPPT tracker is employed as DC source for DVR The shortcoming of conventional inverter sparks an idea of a multilevel inverter based DVR Hence a five level cascaded H bridge multilevel inverter is implemented as voltage source for DVR newline |
Pagination: | xxxii,200p. |
URI: | http://hdl.handle.net/10603/301721 |
Appears in Departments: | Faculty of Electrical Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf.pdf | Attached File | 110.57 kB | Adobe PDF | View/Open |
02_certificates.pdf.pdf | 1.14 MB | Adobe PDF | View/Open | |
03_abstracts.pdf.pdf | 88.22 kB | Adobe PDF | View/Open | |
04_acknowledgements.pdf.pdf | 85.86 kB | Adobe PDF | View/Open | |
05_contents.pdf.pdf | 131.6 kB | Adobe PDF | View/Open | |
06_list_of_tables.pdf.pdf | 90.41 kB | Adobe PDF | View/Open | |
07_list_of_figures.pdf | 98.18 kB | Adobe PDF | View/Open | |
08_list_of_abbreviations.pdf | 123.08 kB | Adobe PDF | View/Open | |
09_chapter1.pdf.pdf | 1.44 MB | Adobe PDF | View/Open | |
10_chapter2.pdf.pdf | 152.16 kB | Adobe PDF | View/Open | |
11_chapter3.pdf.pdf | 1.65 MB | Adobe PDF | View/Open | |
12_chapter4.pdf.pdf | 8.25 MB | Adobe PDF | View/Open | |
13_chapter5.pdf.pdf | 7.98 MB | Adobe PDF | View/Open | |
14_chapter6.pdf.pdf | 3.02 MB | Adobe PDF | View/Open | |
15_conclusion.pdf.pdf | 144.18 kB | Adobe PDF | View/Open | |
16_references.pdf.pdf | 181.7 kB | Adobe PDF | View/Open | |
17_list_of_publications.pdf | 124.17 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 274.3 kB | Adobe PDF | View/Open |
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