基于神经网络的KY变换器光伏系统最大功率跟踪器

2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA) Pub Date : 2015-10-01 DOI:10.1109/ICAMIMIA.2015.7508014

A. Kurniawan, E. Haryanto, A. Masroeri

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引用次数: 7

摘要

光伏发电系统在船舶上的应用可以降低运营成本，减少化石燃料对船舶的污染。为了优化光伏发电系统的效率，必须在系统上实施适当的最大功率点跟踪(MPPT)。MPPT必须具有快速响应能力，以克服由于船舶运动或自然事件引起的太阳辐照度的快速变化。本文提出了一种基于人工神经网络的MPPT与KY变换器相结合的方法。通过计算机仿真验证了该方法的有效性。结果表明，该方法可以优化光伏系统的性能，对太阳辐照度的变化有较快的响应。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle

The application of photovoltaic system on the ship may reduce the operational cost and pollution caused by fossil fuel. In order to optimize the efficiency of the PV system, an appropriate maximum power point tracking (MPPT) must be implemented on the system. The MPPT must have fast response to overcome the rapid changes of solar irradiance due to ship movement or natural occurrence. In this paper, a combination of artificial neural network based MPPT and KY converter is proposed. The proposed method has been validated with a computer based simulation. The results show that the proposed method can optimize the PV system performance with a fast response to the change of sun irradiance.

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2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

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