Implementing GA-ANFIS for Maximum Power Point Tracking in PV System

Nowadays, it has been a developing consideration towards utilization of photovoltaic (PV) system. This paper proposes the Adaptive Neuro-Fuzzy Inference System (ANFIS) and an integrated offline Genetic Algorithm (GA) to track the PV power based on different circumstances due to the various climate c...

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Bibliographic Details
Published in:Indian journal of science and technology 2015-05, Vol.8 (10), p.982-982
Main Authors: Rezvani, Alireza, Izadbakhsh, Maziar, Gandomkar, Majid, Vafaei, Saeed
Format: Article
Language:English
Subjects:
Adaptive systems
Artificial neural networks
Fuzzy logic
Genetic algorithms
Matlab
Maximum power
Photovoltaic cells
Solar cells
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Summary:Nowadays, it has been a developing consideration towards utilization of photovoltaic (PV) system. This paper proposes the Adaptive Neuro-Fuzzy Inference System (ANFIS) and an integrated offline Genetic Algorithm (GA) to track the PV power based on different circumstances due to the various climate changes. Training data in ANFIS are optimized by GA. The proposed controller is accomplished and studied applying Matlab/Simulink software. The results show minimal error of Maximum Power Point (MPP), Optimal Voltage (V sub( mpp)) and superior capability of the suggested method in MPP tracking.
ISSN:0974-6846
0974-5645
DOI:10.17485/ijst/2015/v8i10/51832