Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/458729
Title: | Fuzzy logic and artificial neural network based maximum power point tracking in photo voltaic array under partial shading conditions |
Researcher: | Rajavel A |
Guide(s): | Rathina Prabha N |
Keywords: | Photo-Voltaic Artificial Neural Network Fuzzy Logic Controller |
University: | Anna University |
Completed Date: | 2021 |
Abstract: | not meet the needs. The sustainable energy resources are the alternate newlinechoice. In India, wind and solar energies are the promising resources as they are newlineavailable in plenty. Hence the government of India is investing a large amount in newlinethese two renewable energy sources. newlineIn Photo-Voltaic (PV) system, the maximum power should be newlineobtained from solar array to increase the efficiency of the system. Different newlineMaximum Power Point Tracking (MPPT) algorithms are used to track the newlinemaximum power. This study aims to select the best MPPT algorithm to produce newlineefficient power without any oscillation from PV array. newlineThe problem of oscillation occurs when there is any sudden change in newlineirradiance from the sun. To overcome this issue, Fuzzy Logic Controller (FLC) newlinewith two sets of conditions are defined; one with constant irradiance from the newlinesun and another with variable irradiance from the sun. Each condition defines newlinedifferent set of inputs and generates duty cycle as the output. The algorithm is newlineanalyzed with Buck, Boost and Buck-Boost converter and their responses are newlinecompared under two mentioned conditions. The study shows Buck-Boost and newlineBoost converters are better than Buck converter for the given operating newlinecondition of PV array. The MPPT tracked by the proposed FLC controller is newlinevery close to the operating values in all the irradiance conditions. The power also newlinesettles faster without any oscillation. The result is also validated with digital newlinecontrollers. newlineIn order to improve the accuracy, work is carried with Artificial newlineNeural Network (ANN). A new Online Hiring Algorithm (OHA) is considered newlineand modified as MPPT algorithm. It is implemented using ANN and applied to newlinetrack MPPT newline |
Pagination: | xx,128p. |
URI: | http://hdl.handle.net/10603/458729 |
Appears in Departments: | Faculty of Electrical Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 10.06 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 214.13 kB | Adobe PDF | View/Open | |
03_content.pdf | 14.03 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 7.56 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 152.59 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 168.87 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 620.69 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 814.17 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 522.54 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 215.32 kB | Adobe PDF | View/Open | |
11_chapter 7.pdf | 191.03 kB | Adobe PDF | View/Open | |
12_annexures.pdf | 93.34 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 34.6 kB | Adobe PDF | View/Open |
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