Artificial Fish Swarm Algorithm Based-Maximum Power Generation for Grid-Connected PV Panels

Mingxuan Mao, Li Zhang, Mark Musembi, B. Chong, Qi-chang Duan
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引用次数: 3

Abstract

This paper proposes a novel maximum power point tracking (MPPT) method and a single-phase grid-connected photovoltaic (PV) system using a half-bridge active neutral point clamped (ANPC) inverter. The new MPPT method uses a modified artificial fish swarm algorithm (MAFSA) performed by a boost DC/DC converter. For the ANPC a switching-loss balancing pulse-width modulation scheme is used for control of the inverter. This scheme has shown to increase the maximum power point searching speed and accuracy, and by combining this tracking technique with the inverter, the overall system efficiency is higher the conventional particle swarm optimization (PSO) based-MPPT method. The performance of the proposed system is verified through simulation studies under the different partial shading conditions.
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基于人工鱼群算法的并网光伏板最大功率发电
本文提出了一种新的最大功率点跟踪方法,并采用半桥有源中性点箝位(ANPC)逆变器实现了单相光伏并网系统。新的MPPT方法采用改进的人工鱼群算法(MAFSA),由升压DC/DC变换器执行。ANPC采用开关损耗平衡脉宽调制方式对逆变器进行控制。该方案提高了最大功率点搜索的速度和精度,并将该跟踪技术与逆变器相结合,使系统整体效率高于传统的基于粒子群优化(PSO)的最大功率点跟踪方法。通过不同遮阳条件下的模拟研究,验证了该系统的性能。
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