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Abstract
This paper proposes to estimate the electrical characteristics and maximum power point of a photovoltaic (PV) panel under variable environmental conditions in Şanlıurfa region (southeast of Turkey). Variable environment conditions cause to change of current, voltage and maximum power point (MPP) of PV panels. Under any environmental conditions there is a unique MPP for PV panels, to increase efficiency and reduce cost of energy systems, it is need to determine the maximum power point and electrical characteristics of PV panels. The Artificial Neural Network (ANN) is an improved structure that neurobiologically inspires brain functioning, to determine the effects of all parameters on system, ANN Cascade-forward backpropagation and feed-forward backpropagation algorithm have been used, the installed system performed in Şanlıurfa region and the detailed performance tests have been performed in MATLAB simulation program. The proposed system is the first study by means of installing in Şanlıurfa region and estimating all variables of a PV panel with Cascade-Forward Backpropagation and Feed-Forward Backpropagation.
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Details
1 Harran University, 63000 Sanl?urfa, Turkey
2 Faculty of Electrical and Electronics Engineering, Iskenderun Technical University, 31200 İskenderun/Hatay, Turkey
3 Faculty of Electrical and Electronics Engineering, Cukurova University, 01330 Sar??am/Adana, Turkey