Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking
This paper presents a modified Levy particle swarm optimization (MLPSO) to improve the capability of maximum power point tracking (MPPT) under various partial shading conditions. This method is aimed primarily at resolving the tendency to trap at the local optimum particularly during shading conditi...
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| Format: | Article |
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MDPI AG
2022-10-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/19/7370 |
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| author | Chanuri Charin Dahaman Ishak Muhammad Ammirrul Atiqi Mohd Zainuri Baharuddin Ismail Turki Alsuwian Adam R. H. Alhawari |
| author_facet | Chanuri Charin Dahaman Ishak Muhammad Ammirrul Atiqi Mohd Zainuri Baharuddin Ismail Turki Alsuwian Adam R. H. Alhawari |
| author_sort | Chanuri Charin |
| collection | DOAJ |
| description | This paper presents a modified Levy particle swarm optimization (MLPSO) to improve the capability of maximum power point tracking (MPPT) under various partial shading conditions. This method is aimed primarily at resolving the tendency to trap at the local optimum particularly during shading conditions. By applying a Levy search to the particle swarm optimization (PSO), the randomness of the step size is not limited to a specific value, allowing for full exploration throughout the power-voltage (P-V) curve. Therefore, the problem such as immature convergence or being trapped at a local maximum power point can be avoided. The proposed method comes with great advantages in terms of consistent solutions over various environmental changes with a small number of particles. To verify the effectiveness of the proposed idea, the algorithm was tested on a boost converter of a photovoltaic (PV) energy system. Both simulation and experimental results showed that the proposed algorithm has a high efficiency and fast-tracking speed compared to the conventional HC and PSO algorithm under various shading conditions. Based on the results, it was found that the proposed algorithm successfully converges most rapidly to the global maximum power point (GMPP) and that the tracking of GMPP under complex partial shading is guaranteed. Furthermore, the average efficiency for all test conditions was 99% with a tracking speed of 1.5 s to 3.0 s and an average output steady-state oscillation of 0.89%. |
| first_indexed | 2024-03-09T21:45:57Z |
| format | Article |
| id | doaj.art-61377881beab4ea3ac7c3026e7f1edbc |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T21:45:57Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-61377881beab4ea3ac7c3026e7f1edbc2023-11-23T20:17:53ZengMDPI AGEnergies1996-10732022-10-011519737010.3390/en15197370Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point TrackingChanuri Charin0Dahaman Ishak1Muhammad Ammirrul Atiqi Mohd Zainuri2Baharuddin Ismail3Turki Alsuwian4Adam R. H. Alhawari5School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Pulau Pinang 14300, MalaysiaSchool of Electrical and Electronic Engineering, Universiti Sains Malaysia, Pulau Pinang 14300, MalaysiaDepartment of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Selangor 43600, MalaysiaFaculty of Electrical Engineering and Technology, Universiti Malaysia Perlis, Perlis 02600, MalaysiaElectrical Engineering Department, College of Engineering, Najran University, Najran 11001, Saudi ArabiaElectrical Engineering Department, College of Engineering, Najran University, Najran 11001, Saudi ArabiaThis paper presents a modified Levy particle swarm optimization (MLPSO) to improve the capability of maximum power point tracking (MPPT) under various partial shading conditions. This method is aimed primarily at resolving the tendency to trap at the local optimum particularly during shading conditions. By applying a Levy search to the particle swarm optimization (PSO), the randomness of the step size is not limited to a specific value, allowing for full exploration throughout the power-voltage (P-V) curve. Therefore, the problem such as immature convergence or being trapped at a local maximum power point can be avoided. The proposed method comes with great advantages in terms of consistent solutions over various environmental changes with a small number of particles. To verify the effectiveness of the proposed idea, the algorithm was tested on a boost converter of a photovoltaic (PV) energy system. Both simulation and experimental results showed that the proposed algorithm has a high efficiency and fast-tracking speed compared to the conventional HC and PSO algorithm under various shading conditions. Based on the results, it was found that the proposed algorithm successfully converges most rapidly to the global maximum power point (GMPP) and that the tracking of GMPP under complex partial shading is guaranteed. Furthermore, the average efficiency for all test conditions was 99% with a tracking speed of 1.5 s to 3.0 s and an average output steady-state oscillation of 0.89%.https://www.mdpi.com/1996-1073/15/19/7370photovoltaicpartial shading conditionglobal maximum power pointlocal maximum power pointdynamic irradiance change |
| spellingShingle | Chanuri Charin Dahaman Ishak Muhammad Ammirrul Atiqi Mohd Zainuri Baharuddin Ismail Turki Alsuwian Adam R. H. Alhawari Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking Energies photovoltaic partial shading condition global maximum power point local maximum power point dynamic irradiance change |
| title | Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking |
| title_full | Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking |
| title_fullStr | Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking |
| title_full_unstemmed | Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking |
| title_short | Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking |
| title_sort | modified levy based particle swarm optimization mlpso with boost converter for local and global point tracking |
| topic | photovoltaic partial shading condition global maximum power point local maximum power point dynamic irradiance change |
| url | https://www.mdpi.com/1996-1073/15/19/7370 |
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