An intelligent modeling of photovoltaic comparison among NAR, NARX, and nonlinear

Nonlinear device recognition simulation for photovoltaic (PV) temperature panels has been done in this work. Initially, experimental work was derived from experimental work to obtain input and output data as PV module temperature. Subsequently, nonlinear self-regressive (NAR), nonlinear self-regressive exogenous (NARX) and nonlinear input-output models represented as device recognition methods for estimating the PV panel temperature as an output of the system. Both modeling techniques checked using a MSE (mean square error). The efficiency of both approaches was compared to the awareness of which technique is the better. Lastly, the best results obtained showed that NARX approach followed by the NAR.