Design and Analysis of Optimal Maximum Power Point Tracking Algorithm using ANFIS Controller for PV Systems

P. Latha Mangeshkar, T. Gowri Manohar
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Abstract

The Photovoltaic cell is considered as one of the most promising devices in photovoltaic generation. It is used to convert solar energy into electrical energy. Nowadays, Photovoltaic generation is developing more rapidly as a renewable energy source. But, the drawback is that Photovoltaic generation is discontinuous because of it depends on the weather conditions. This paper presents a high performance tracking method for maximum power generated by photovoltaic (PV) systems. Based on adaptive Neuro-Fuzzy inference systems (ANFIS), this method combines the learning abilities of artificial neural networks and the ability of fuzzy logic to handle imprecise data. It is able to handle non-linear and time varying problems hence making it suitable for accurate maximum power point tracking (MPPT) to ensure PV systems work effectively. The performance of the proposed method is compared to that of a fuzzy logic based MPPT algorithm to demonstrate its effectiveness.
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基于ANFIS控制器的光伏系统最优最大功率跟踪算法设计与分析
光伏电池被认为是光伏发电中最有前途的器件之一。它被用来把太阳能转换成电能。目前,光伏发电作为一种可再生能源发展较快。但是,缺点是光伏发电是不连续的,因为它取决于天气条件。提出了一种高性能的光伏发电系统最大功率跟踪方法。该方法基于自适应神经模糊推理系统(ANFIS),将人工神经网络的学习能力与模糊逻辑处理不精确数据的能力相结合。它能够处理非线性和时变问题,因此适用于精确的最大功率点跟踪(MPPT),以确保光伏系统有效工作。通过与基于模糊逻辑的MPPT算法的性能比较,验证了该方法的有效性。
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