Determination of the PV Module Surface Temperature Based on Neural Network Using Solar Radiation and Surface Temperature: Recent Development | Chapter 14 | Recent Advances in Science and Technology Research Vol. 1

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.

Author(s) Details

Dr. Aiat Hegazy
Department Solar Energy, National Research Centre, El Buhouth St., Dokki, Giza, Egypt.

Dr. E. T. El Shenawy
Department Solar Energy, National Research Centre, El Buhouth St., Dokki, Giza, Egypt.

Dr. M. A. Ibrahim
Department Solar Energy, National Research Centre, El Buhouth St., Dokki, Giza, Egypt.

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