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.

Details

Title
Estimation of Electrical Characteristics and Maximum Power Point of Photovoltaic Panel
Author
Yılmaz, Ünal 1 ; Türksoy, Ömer 2 ; İbrikçi, Turgay 3 ; Teke, Ahmet 3 

 Harran University, 63000 Sanl?urfa, Turkey 
 Faculty of Electrical and Electronics Engineering, Iskenderun Technical University, 31200 İskenderun/Hatay, Turkey 
 Faculty of Electrical and Electronics Engineering, Cukurova University, 01330 Sar??am/Adana, Turkey 
Pages
255-265
Section
Regular paper
Publication year
2017
Publication date
2017
Publisher
Engineering and Scientific Research Groups
e-ISSN
11125209
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2272186618
Copyright
© 2017. This article is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.