Design and Analysis of Optimal Maximum Power Point Tracking Algorithm using ANFIS Controller for PV Systems
DOI:
https://doi.org/10.51983/ajes-2019.8.3.2103Keywords:
Maximum Power Point Tracking (MPPT), Photovoltaic (PV) Systems, Fuzzy Logic Controller (FLC), Adaptive Neuro-Fuzzy Inference Systems (ANFIS)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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