A Critical Review on the Estimation Techniques of the Solar PV Cell’s Unknown Parameters

Papul Changmai, Sunil Deka, Shashank Kumar, Thanikanti Sudhakar Babu, Belqasem Aljafari and Benedetto Nastasi ()
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Papul Changmai: Electrical and Electronics Engineering Department, Assam Don Bosco University, Guwahati 781039, India
Sunil Deka: Electrical and Electronics Engineering Department, Assam Don Bosco University, Guwahati 781039, India
Shashank Kumar: Electronics and Electrical Engineering Department, Indian Institute of Technology Guwahati (IIT), Guwahati 781017, India
Thanikanti Sudhakar Babu: Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology (CBIT), Hyderabad 500075, India
Belqasem Aljafari: Department of Electrical Engineering, College of Engineering, Najran University, Najran 11001, Saudi Arabia
Benedetto Nastasi: Department of Planning, Design and Technology of Architecture, Sapienza University of Rome, 00196 Rome, Italy

Energies, 2022, vol. 15, issue 19, 1-20

Abstract: To meet the exponentially growing demand for clean and green energy, the solar photovoltaic (PV) system’s importance is increasing day by day, for which PV modeling is considered to be one of the most important work in the current state-of-the-art methods. To effectively model a PV system, accurate PV parameter estimation is of the utmost importance. In line with this, although the values of some of the parameters are provided in the manufacturer’s datasheet, the values of unknown parameters, such as shunt resistance, series resistance, the diode ideality factor, photo-generated current and diode saturation current, are not provided. To estimate these values a lot of algorithms are already reported in the literature. After careful observation of all the reported algorithms, a few best-reported algorithms are identified and their performances are compared with respect to accuracy, convergence issues, computational complexity and thermal stability. All kind of algorithms, such as numerical, analytical and evolutionary algorithms, are considered in this study, and only the best reported algorithms are considered for the comparison.

Keywords: solar photovoltaic; parameter estimation; single-diode model; double-diode model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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