Estimation of Electrical Characteristics and Maximum Power Point of Photovoltaic Panel

YILMAZ Ü., Turksoy O., İBRİKÇİ T., TEKE A.

JOURNAL OF ELECTRICAL SYSTEMS, cilt.13, sa.2, ss.255-265, 2017 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 13 Sayı: 2
  • Basım Tarihi: 2017
  • Dergi Adı: JOURNAL OF ELECTRICAL SYSTEMS
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
  • Sayfa Sayıları: ss.255-265
  • Çukurova Üniversitesi Adresli: Evet

Özet

This paper proposes to estimate the electrical characteristics and maximum power point of a photovoltaic (PV) panel under variable environmental conditions in Sanlrurfa 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 Sanlrurfa 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 Sanlrurfa region and estimating all variables of a PV panel with Cascade-Forward Backpropagation and Feed-Forward Backpropagation.