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Effective utilisation and efficient maximum power extraction in partially shaded photovoltaic systems using minimum-distance-average-based clustering algorithm

机译:使用基于最小距离平均的聚类算法在部分阴影光伏系统中进行有效利用和有效最大功率提取

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摘要

The reduction in power depends on module interconnection scheme and shading pattern. Different interconnection schemes are used to reduce the losses caused by partial shading. This study presents a minimum-distance-average-based clustering algorithm for the photovoltaic (PV) arrays that can improve the PV power under different shading conditions. The PV array is configured based on a novel clustering algorithm in wireless sensor networks based on sensor node deployment location coordinates. Various cases such as short narrow, short wide, long narrow and long wide have been analysed and their performances were discussed. The proposed method facilitates maximum power extraction by distributing the effect of shading over the entire array thereby reducing the mismatch losses caused by partial shading conditions. The performance of the system is investigated for different shading conditions. Also Monte Carlo estimator was used to improve the impact of the investigation by varying solar irradiance values and the results are presented to show the successful working of the proposed scheme.
机译:功耗的降低取决于模块互连方案和阴影图案。使用不同的互连方案来减少由部分阴影引起的损耗。这项研究提出了一种用于光伏(PV)阵列的基于最小距离平均的聚类算法,可以在不同的阴影条件下提高PV功率。基于传感器节点部署位置坐标的无线传感器网络中的新型聚类算法,可配置PV阵列。分析了诸如短窄,短宽,长窄和长宽之类的各种情况,并讨论了它们的性能。所提出的方法通过在整个阵列上分布阴影效应来促进最大功率提取,从而减少了由部分阴影条件引起的失配损耗。针对不同的遮光条件研究了系统的性能。此外,还通过更改太阳辐照度值使用了蒙特卡洛估计量来改善调查的影响,并给出了结果,以表明所提出方案的成功工作。

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