修车大队一品楼qm论坛51一品茶楼论坛,栖凤楼品茶全国楼凤app软件 ,栖凤阁全国论坛入口,广州百花丛bhc论坛杭州百花坊妃子阁

oe1(光电查) - 科学论文

2 条数据
?? 中文（中国） ▾

  • [IEEE 2019 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America) - Gramado, Brazil (2019.9.15-2019.9.18)] 2019 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America) - Particle Swarm Optimization of the GMPPT of Photovoltaic Energy Generation under Different Partial Shadding Conditions

    摘要： The performance of a photovoltaic (PV) generation system (PGS) is directly associated with the irradiation incidence over the PV panel and the maximum energy will be delivered only for full panel illumination. However, when the PV panel (or strings of panels) operates under a partial shadowing condition (PSC), only a percentage of the maximum power will be delivered. This power can be even lower without a proper configuration of the conversion system. Therefore, we propose a partile swarm optimization (PSO) of the conversion system which improves the Maximum Power Point Tracking (MPPT) and ensures that the maximum power will be delivered despite of the partial shadowing condition.

    关键词： Maximum Power Point Tracking (MPPT),Global Maximum Power Point (GMPP),PSO algorithm,photovoltaic system

    更新于2025-09-12 10:27:22

  • A Lipschitz Optimization Based MPPT Algorithm for Photovoltaic System under Partial Shading Condition

    摘要： The power–voltage curve of a photovoltaic (PV) array shows multiple power peaks under partially shading conditions (PSCs). Hence, conventional maximum power point tracking (MPPT) algorithms can not guarantee the maximum power output of the PV array. In this study, a novel Lipschitz optimization (LIPO) MPPT algorithm, which is effective under PSCs, is proposed and analyzed. Its tracking speed is very fast and tracking efficiency is above 98%. The characteristics of a PV array under PSCs are first analyzed and then the working principle of the proposed LIPO MPPT algorithm is explained. In order to validate the performance of the proposed algorithm, two popular MPPT algorithms, i.e., the modified particle swarm optimization (M-PSO) algorithm and the modified firefly optimization (M-firefly) algorithm, are chosen to compare with it. All three algorithms are fulfilled and compared with each other through both simulations and experiments and the results show that the proposed MPPT algorithm has good performance.

    关键词： Global maximum power point (GMPP),maximum power point tracking (MPPT),Lipschitz optimization (LIPO),partially shaded condition (PSC)

    更新于2025-09-11 14:15:04