Optimal parameters selection of particle swarm optimization based global maximum power point tracking of partially shaded PV

Bibliographic Details
Parent link:Journal of Physics: Conference Series
Vol. 1399 : Applied Physics, Information Technologies and Engineering – APITECH-2019.— 2019.— [022032, 7 р.]
Main Author: Obukhov S. G. Sergey Gennadievich
Corporate Author: Национальный исследовательский Томский политехнический университет Инженерная школа энергетики Отделение электроэнергетики и электротехники (ОЭЭ)
Other Authors: Ibrahim Ahmed I. M. Ibrahim Mohamed, Aboelsaud Raef S. S. A. Siam Sayed Ahmed
Summary:Title screen
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.
Published: 2019
Subjects:
Online Access:http://earchive.tpu.ru/handle/11683/57639
https://doi.org/10.1088/1742-6596/1399/2/022032
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=661638