Improvement of convergence speed of particle swarm optimization algorithm: application to Maximum PowerPoint Tracking control of a photovoltaic generator

The photovoltaic system (PVS) studied in this article consists of a photovoltaic generator (PVG) supplying a battery through a step-down chopper. The objective of the work is to speed up the convergence of the particle swarm algorithm in order to find the maximum power point of the photovoltaic gene...

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Published in2022 IEEE International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM) Vol. 4; pp. 1 - 7
Main Authors Khady Diop, Dieng Ndeye, Oumar, Ba, Boubacar, Niang, Lamine, Thiaw, Samba, Gueye, Hadj Mbaye, Ndiaye El
Format Conference Proceeding
LanguageEnglish
Published IEEE 26.10.2022
Subjects
battery
DC-DC power converters
Generators
Heuristic algorithms
Particle swarm optimization
photovoltaic generator
Photovoltaic systems
Radiation effects
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Summary:The photovoltaic system (PVS) studied in this article consists of a photovoltaic generator (PVG) supplying a battery through a step-down chopper. The objective of the work is to speed up the convergence of the particle swarm algorithm in order to find the maximum power point of the photovoltaic generator. For this, a modified version of the Particle Swarm Optimization (PSO) algorithm suitable for our PVS is applied to the control of the DC-DC converter in order to accelerate de maximum power point of the generator. The developed algorithm is simulated in Matlab-Simulink for uniform dynamic irradiation and temperature on the PVG. The obtained results show that for an estimated MPPT control efficiency of at least 99.7 %, the improved PSO algorithm converges to near MPP with a smaller number of iterations than the PSO without improvement in all test cases.
DOI:10.1109/CISTEM55808.2022.10043909