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

Sergey Obukhov, Ahmed Ibrahim, Raef Aboelsaud

Результат исследований: Материалы для журнала

Аннотация

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.

Язык оригиналаАнглийский
Номер статьи022032
ЖурналJournal of Physics: Conference Series
Том1399
Номер выпуска2
DOI
СостояниеОпубликовано - 5 дек 2019
СобытиеInternational Scientific Conference on Applied Physics, Information Technologies and Engineering 2019, APITECH 2019 - Krasnoyarsk, Российская Федерация
Продолжительность: 25 сен 201927 сен 2019

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Fingerprint Подробные сведения о темах исследования «Optimal parameters selection of particle swarm optimization based global maximum power point tracking of partially shaded PV». Вместе они формируют уникальный семантический отпечаток (fingerprint).

  • Цитировать