Particle swarm optimization for MPPT : simulation and analysis
Energy conversion efficiency of solar photovoltaic (PV) is low. Maximum Power Point Tracking (MPPT) is one of the most economical ways to increase the efficiency of solar photovoltaic . The main function of this MPPT is to ensure the maximum power output extracted from the PV array. This project is...
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my-utm-ep.488232020-06-24T03:36:26Z Particle swarm optimization for MPPT : simulation and analysis 2014-06 Daud, Noor Dzulaikha TK Electrical engineering. Electronics Nuclear engineering Energy conversion efficiency of solar photovoltaic (PV) is low. Maximum Power Point Tracking (MPPT) is one of the most economical ways to increase the efficiency of solar photovoltaic . The main function of this MPPT is to ensure the maximum power output extracted from the PV array. This project is to design Particle Swarm Optimization (PSO) algorithm as MPPT controller to extract maximum power from the PV module under normal shading conditions. The proposed technique for this project is based on the intelligence algorithm to control power output from the PV module and dc-dc power converter should be switched to obtain the maximum power output. The results show that the power oscillation at steady state is significantly diminished which can improve the PV conversion efficiency. The parameters of the PSO algorithm will be changed in order to see its tracking performance. Simulation of the PV module, PSO algorithm and dc-dc boost converter are done, using MATLAB-Simulink software. It is found that the change of PSO algorithm parameters gives the better result on the convergence speed and ability to find the optimum point. 2014-06 Thesis http://eprints.utm.my/id/eprint/48823/ http://eprints.utm.my/id/eprint/48823/25/NoorDzulaikhaDaudMFKE2014.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:83854 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering |
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TK Electrical engineering Electronics Nuclear engineering |
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TK Electrical engineering Electronics Nuclear engineering Daud, Noor Dzulaikha Particle swarm optimization for MPPT : simulation and analysis |
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Energy conversion efficiency of solar photovoltaic (PV) is low. Maximum Power Point Tracking (MPPT) is one of the most economical ways to increase the efficiency of solar photovoltaic . The main function of this MPPT is to ensure the maximum power output extracted from the PV array. This project is to design Particle Swarm Optimization (PSO) algorithm as MPPT controller to extract maximum power from the PV module under normal shading conditions. The proposed technique for this project is based on the intelligence algorithm to control power output from the PV module and dc-dc power converter should be switched to obtain the maximum power output. The results show that the power oscillation at steady state is significantly diminished which can improve the PV conversion efficiency. The parameters of the PSO algorithm will be changed in order to see its tracking performance. Simulation of the PV module, PSO algorithm and dc-dc boost converter are done, using MATLAB-Simulink software. It is found that the change of PSO algorithm parameters gives the better result on the convergence speed and ability to find the optimum point. |
format |
Thesis |
qualification_level |
Master's degree |
author |
Daud, Noor Dzulaikha |
author_facet |
Daud, Noor Dzulaikha |
author_sort |
Daud, Noor Dzulaikha |
title |
Particle swarm optimization for MPPT : simulation and analysis |
title_short |
Particle swarm optimization for MPPT : simulation and analysis |
title_full |
Particle swarm optimization for MPPT : simulation and analysis |
title_fullStr |
Particle swarm optimization for MPPT : simulation and analysis |
title_full_unstemmed |
Particle swarm optimization for MPPT : simulation and analysis |
title_sort |
particle swarm optimization for mppt : simulation and analysis |
granting_institution |
Universiti Teknologi Malaysia, Faculty of Electrical Engineering |
granting_department |
Faculty of Electrical Engineering |
publishDate |
2014 |
url |
http://eprints.utm.my/id/eprint/48823/25/NoorDzulaikhaDaudMFKE2014.pdf |
_version_ |
1747817480371306496 |