الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Photovoltaic energy is considered to be one of the most promising technologies which can greatly contribute to future energy supply because it is pollution-&ee essentially inexhaustible and broadly recourse-sunlight. In this work the parameters, which affect the photovoltaic panel performance, are explained &om the point of view of electronic devices. Also the artificial neural networks were investigated as a powerful tool for modeling the effects of environmental parameters on the cell operating temperature due to its ability in function approximation (modeling) and handling nonlinear or complex data.
This work was also motivated by the desire to present a modified neural network model to simulate the I-V characteristics of a photo voltaic (PV) cell and to predict the solar cell operating temperature so as to investigate the temperature and irradiance re~ behavior in order to characterize the perfonnance of photo voltaic arrays in their actual environment of use.
It should be remarked that, in the experimental work. a single encapsulated cell similar to the ones in a PV module, was available to be tested under different operating conditions. The outdoors current _ voltage measurements and other cell affecting parameters such as: ambient temperature, cell temperature, wind speed, air mass, and irradiance were performed on cloudless days. A trained feed forward multi-layer perceptron neural network was used to learn the interrelations of these parameters and then to predict the operating temperature for different cells. The results obtained were compared favorably with those of the conventional multiple regression model.