The paper presents an artificial intelligence (AI) technique for the estimation of the equivalent circuit parameters of photovoltaic (PV) modules. The parameters considered in the study are the series resistance, shunt resistance, and diode ideality factor. Adaptive neuro-fuzzy inference systems (ANFIS) and artificial neural networks (ANN) are independently employed for the estimation process. Training data for both paradigms are extracted from analytical solution of the PV mathematical model. Comparison of the testing results signifies that ANN outperforms ANFIS in estimating the required parameters.
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Salem et al. (2014) studied this question.
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