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Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions

机译:组合粒子群优化与摄动和观测方法在部分遮蔽条件下光伏系统中MPPT的应用

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This paper explains the development of a new algorithm for maximum power point tracking (MPPT) in large PV systems under partial shading conditions (PSC). The new algorithm combines the use of particle swarm optimization (PSO) for MPPT during the initial stages of tracking and then employs the traditional perturb and observe (PO) method at the final stages. The methodology has been first simulated in two different PV configurations under varying shading patterns and experimentally verified using a microcontroller based experimental system. The integration of swarm intelligence with PO algorithm is shown to yield faster convergence to the global maximum power point (GMPP) than when the two methods are individually used. The oscillations in the output power, voltage and current of the PV system with the proposed method are the least when compared to the ones obtained during PSO based MPPT. (C) 2014 Elsevier Ltd. All rights reserved.
机译:本文解释了在部分阴影条件(PSC)下大型光伏系统中最大功率点跟踪(MPPT)的新算法的开发。新算法结合了在跟踪的初始阶段对MPPT使用粒子群优化(PSO),然后在最后阶段采用了传统的扰动和观察(PO)方法。该方法首先在两种不同的PV配置下以不同的阴影模式进行了仿真,并使用基于微控制器的实验系统进行了实验验证。与单独使用两种方法相比,将群体智能与PO算法集成在一起可以更快地收敛到全局最大功率点(GMPP)。与基于PSO的MPPT所获得的结果相比,所提出的方法在光伏系统的输出功率,电压和电流中的振荡最小。 (C)2014 Elsevier Ltd.保留所有权利。

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