Data-Driven Photovoltaic System Modeling Based on Nonlinear System Identification
Joint Authors
Alqahtani, Ayedh
Alsaffar, Mohammad
El-Sayed, Mohamed
Alajmi, Bader
Source
International Journal of Photoenergy
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-30
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Solar photovoltaic (PV) energy sources are rapidly gaining potential growth and popularity compared to conventional fossil fuel sources.
As the merging of PV systems with existing power sources increases, reliable and accurate PV system identification is essential, to address the highly nonlinear change in PV system dynamic and operational characteristics.
This paper deals with the identification of a PV system characteristic with a switch-mode power converter.
Measured input-output data are collected from a real PV panel to be used for the identification.
The data are divided into estimation and validation sets.
The identification methodology is discussed.
A Hammerstein-Wiener model is identified and selected due to its suitability to best capture the PV system dynamics, and results and discussion are provided to demonstrate the accuracy of the selected model structure.
American Psychological Association (APA)
Alqahtani, Ayedh& Alsaffar, Mohammad& El-Sayed, Mohamed& Alajmi, Bader. 2016. Data-Driven Photovoltaic System Modeling Based on Nonlinear System Identification. International Journal of Photoenergy،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1106455
Modern Language Association (MLA)
Alqahtani, Ayedh…[et al.]. Data-Driven Photovoltaic System Modeling Based on Nonlinear System Identification. International Journal of Photoenergy No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1106455
American Medical Association (AMA)
Alqahtani, Ayedh& Alsaffar, Mohammad& El-Sayed, Mohamed& Alajmi, Bader. Data-Driven Photovoltaic System Modeling Based on Nonlinear System Identification. International Journal of Photoenergy. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1106455
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1106455