Parameter Estimation Techniques for Photovoltaic System Modeling

Manish Kumar Singla, Jyoti Gupta, Parag Nijhawan, Parminder Singh, Nimay Chandra Giri, Essam Hendawi and Mohamed I. Abu El-Sebah ()
Additional contact information
Manish Kumar Singla: Department of Interdisciplinary Courses in Engineering, Chitkara University Institute of Engineering & Technology, Chitkara University, Rajpura 140401, India
Jyoti Gupta: Department of Computer Science, Shree Guru Gobind Singh Tricentenary University, Gurugram 122505, India
Parag Nijhawan: Electrical and Instrumentation Engineering Department, Thapar Institute of Engineering and Technology, Patiala 147004, India
Parminder Singh: Chemical Engineering Department, Thapar Institute of Engineering and Technology, Patiala 147004, India
Nimay Chandra Giri: Department of Electronics and Communication Engineering, Centurion University of Technology and Management, Jatni 752050, India
Essam Hendawi: Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia
Mohamed I. Abu El-Sebah: Department of Power Electronics and Energy Conversion, Electronics Research Institute, Cairo 11796, Egypt

Energies, 2023, vol. 16, issue 17, 1-16

Abstract: In improving PV system performance, the parameters associated with electrical photovoltaic equivalent models play a pivotal role. However, due to the increased mathematical complexities and non-linear traits of PV cells, the precise prediction of these parameters is a challenging task. To estimate the parameters associated with PV models, a reliable, robust, and accurate optimization technique is needed. This paper introduces a new algorithm, Rat Swarm Optimizer (RSO), for obtaining the optimum PV cell and module parameters. The proposed method maintains an adequate balance between the exploration and exploitation phases to overcome premature particle issues. The results obtained using RSO are compared with those of other algorithms, i.e., Particle Swarm Optimization (PSO), Ant Lion Optimizer (ALO), Salp Swarm Algorithm (SSA), Harris Hawks Optimization (HHO), and Grasshopper Optimization (GOA), in this work. The modified one-diode model (MODM) and modified two-diode model (MTDM) are used to analyze the parameters of the mono-crystalline PV cell using the suggested RSO. The obtained findings imply that the parameters estimated by the suggested RSO are more accurate than those calculated by the other algorithms taken into consideration in the paper. The statistical results are compared, and it is clear that RSO is a very accurate, fast, and dependable approach for the parameter estimation of PV cells.

Keywords: modified one-diode model; modified two-diode model; parameter estimation; optimization; sustainable energy; statistical tests (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: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/17/6280/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/17/6280/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:17:p:6280-:d:1228216

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().