Please use this identifier to cite or link to this item: http://earchive.tpu.ru/handle/11683/57639
Title: Optimal parameters selection of particle swarm optimization based global maximum power point tracking of partially shaded PV
Authors: Obukhov, Sergey Gennadievich
Ibrahim Ahmed, Ibrahim Mohamed
Aboelsaud Raef, Siam Sayed Ahmed
Keywords: оптимальные параметры
Issue Date: 2019
Publisher: IOP Publishing
Citation: Obukhov S. G. Optimal parameters selection of particle swarm optimization based global maximum power point tracking of partially shaded PV / S. G. Obukhov, I. M. Ibrahim Ahmed, S. S. A. Aboelsaud Raef // Journal of Physics: Conference Series. — 2019. — Vol. 1399 : Applied Physics, Information Technologies and Engineering – APITECH-2019 : International Scientific Conference, 25–27 September 2019, Krasnoyarsk, Russian Federation : [proceedings]. — [022032, 7 р.].
Abstract: This paper presents optimal parameters selection of particle swarm optimization (PSO) algorithm for determining the global maximum power point tracking of photovoltaic array under partially shaded conditions. Under partial shading, the power-voltage characteristics have a more complex shape with several local peaks and one global peak. The two proposed controllers include dynamic Particle Swarm Optimization, and constant particle swarm optimization. The developed algorithms are implemented in MATLAB/Simulink platform, and their performances are evaluated. The results indicate that the dynamic particle swarm optimization algorithm can very fast track the GMPP within 128 ms for different shading conditions. In addition, the average tracking efficiency of the proposed algorithm is higher than 99.89%, which provides good prospects to apply this algorithm in the control search unit for the global maximum power point in stations.
URI: http://earchive.tpu.ru/handle/11683/57639
Appears in Collections:Материалы конференций

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