Determination of the PV Module Surface Temperature Based on Neural Network Using Solar Radiation and Surface Temperature: Recent Development

Different attempts have been carried out to determine the PV module surface temperatures using
mathematical models of the PV module, empirical formula and by neural networks. Neural network
(NN) doesn’t require any analysis of the system or scientific details; it only needs data from the
system for training purposes. The present research describes the estimation of the PV module
surface temperature using NN based on measured ambient temperatures and incident solar radiation.
The NN is composed of input layer with two inputs (solar radiation and ambient temperature), hidden
layer that has eight neurons and output layer to estimate the PV module surface temperature. Error
back propagation algorithm was used to train the NN. The result showed that, the estimation accuracy
of the PV module surface temperatures by the NN reached more than 96% of the measured values.