Comparison Study Between Improved JAYA and Particle Swarm Optimization PSO Algorithms for Parameter Extraction of Photovoltaic Module Based on Experimental Test

2020 ◽  
pp. 210-221
Author(s):  
Y. Rehouma ◽  
Z. Tir ◽  
A. Gacem ◽  
F. Rehouma ◽  
M. A. Hamida ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Experimental Test ◽  
Particle Swarm ◽  
Parameter Extraction ◽  
Photovoltaic Module ◽  
Comparison Study ◽  
Swarm Optimization

scholarly journals Photovoltaic Module Array Global Maximum Power Tracking Combined with Artificial Bee Colony and Particle Swarm Optimization Algorithm

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 603 ◽  
Author(s):  
Kuei-Hsiang Chao ◽  
Cheng-Chieh Hsieh
Keyword(s):  
Particle Swarm Optimization ◽  
Artificial Bee Colony ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Global Maximum ◽  
Photovoltaic Module ◽  
Swarm Optimization ◽  
Bee Colony ◽  
Learning Factor

In this study, the output characteristics of partial modules in a photovoltaic module array when subject to shading were first explored. Then, an improved particle swarm optimization (PSO) algorithm was applied to track the global maximum power point (MPP), with a multi-peak characteristic curve. The improved particle swarm optimization algorithm proposed, combined with the artificial bee colony (ABC) algorithm, was used to adjust the weighting, cognition learning factor, and social learning factor, and change the number of iterations to enhance the tracking performance of the MPP tracker. Finally, MATLAB software was used to carry out a simulation and prove the improved that the PSO algorithm successfully tracked the MPP in the photovoltaic array output curve with multiple peaks. Its tracking performance is far superior to the existing PSO algorithm.

Parameter extraction of solar cells using particle swarm optimization

2009 ◽  
Vol 105 (9) ◽  
pp. 094502 ◽  
Author(s):  
Meiying Ye ◽  
Xiaodong Wang ◽  
Yousheng Xu
Keyword(s):  
Particle Swarm Optimization ◽  
Solar Cells ◽  
Particle Swarm ◽  
Parameter Extraction ◽  
Swarm Optimization

scholarly journals Maximum Power Point Tracking Method Based on Modified Particle Swarm Optimization for Photovoltaic Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Kuei-Hsiang Chao ◽  
Long-Yi Chang ◽  
Hsueh-Chien Liu
Keyword(s):  
Particle Swarm Optimization ◽  
Maximum Power Point Tracking ◽  
Particle Swarm ◽  
Maximum Power ◽  
Photovoltaic Module ◽  
Maximum Power Point ◽  
Swarm Optimization ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

This study investigated the output characteristics of photovoltaic module arrays with partial module shading. Accordingly, we presented a maximum power point tracking (MPPT) method that can effectively track the global optimum of multipeak curves. This method was based on particle swarm optimization (PSO). The concept of linear decreases in weighting was added to improve the tracking performance of the maximum power point tracker. Simulation results were used to verify that this method could successfully track maximum power points in the output characteristic curves of photovoltaic modules with multipeak values. The results also established that the performance of the modified PSO-based MPPT method was superior to that of conventional PSO methods.

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