光伏系统部分遮阳条件下智能最大功率跟踪器的性能研究

A. Eltamaly
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引用次数: 14

摘要

光伏组件上的部分遮阳减少了光伏系统的发电功率,而不是每个组件单独产生的最大功率。遮阳的光伏组件对未遮阳的光伏组件起负载作用,这可能导致热点。为了减轻部分遮阳的影响,应该在每个光伏模块之间连接旁路二极管。将几个光伏模块连接在一起,在部分遮阳条件下产生多个峰值(一个全局峰值(GP)和多个局部峰值(LP))。最大功率点跟踪器(MPPT)传统技术的设计遵循GP,但他们停留在lp,如模糊逻辑控制器(FLC)。本文利用遗传算法的改进粒子群算法(MPSO)对任意工况下的GP进行跟踪。对MPSO技术进行了研究,并与FLC技术进行了比较,证明了该技术在各种工况下的优越性。利用Matlab/Simulink与PSIM的联合仿真,对部分遮阳条件下的光伏系统进行了建模。仿真结果表明,MPSO技术比FLC技术更有效地跟踪GP。在遮阳条件下,MPSO技术比FLC技术产生的功率显著增加。
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Performance of smart maximum power point tracker under partial shading conditions of PV systems
Partial shading on PV modules reduces the generated power of the PV system than the maximum power generated from each module separately. The shaded PV module acts as a load to unshaded ones which can lead to hot-spot. To alleviate the effect of partial shading, bypass diodes should be connected across each PV modules. Connecting several PV modules together produces multiple peaks (One global peak (GP) and multiple local peaks (LP)) on partial shading conditions. Maximum power point tracker (MPPT) conventional techniques are designed to follow the GP but they stuck around LPs such as fuzzy logic controller (FLC). In this paper, modified particle swarm optimization (MPSO) using genetic algorism has been used to follow the GP under any operating conditions. MPSO has been studied and compared with FLC technique to show the superiority of this technique under all operating conditions. Co-simulation between Matlab/Simulink and PSIM has been used to model the PV system under partial shading conditions. The simulation results show that the MPSO technique is more effective than FLC in following the GP. The generated power increases considerably with MPSO than FLC technique in shading conditions.
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