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Performance analysis of neural network and fuzzy logic based MPPT techniques for solar PV systems

机译:基于神经网络和基于模糊逻辑的MPPT技术在太阳能光伏系统中的性能分析

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The maximum power point tracking (MPPT) technique in the photovoltaic (PV) system is used to achieve maximum power through the solar PV system. Therefore, the interest is generated to design a more effective and efficient MPPT to achieve maximum power transfer to the load. In this context, two MPPT techniques, i.e. artificial neural network (ANN) and fuzzy logic control (FLC) are implemented and their performance is analysed. Both the MPPT techniques are investigated in terms of efficiency and response and they are developed in MATLAB/Simulink environment. Their performance is investigated under variable irradiation conditions and found satisfactory for both the techniques.
机译:光伏(PV)系统中的最大功率点跟踪(MPPT)技术用于通过太阳能PV系统获得最大功率。因此,引起了人们的兴趣,以设计一种更有效的MPPT,以实现向负载的最大功率传输。在这种情况下,实现了两种MPPT技术,即人工神经网络(ANN)和模糊逻辑控制(FLC),并对其性能进行了分析。两种MPPT技术都在效率和响应方面进行了研究,并且都是在MATLAB / Simulink环境中开发的。在可变辐照条件下研究了它们的性能,发现对两种技术均令人满意。

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