Implementation of a Novel Tabu Search Optimization Algorithm to Extract Parasitic Parameters of Solar Panel

Naveena Bhargavi Repalle, Pullacheri Sarala, Lucian Mihet-Popa, Shashidhar Reddy Kotha and Nagalingam Rajeswaran
Additional contact information
Naveena Bhargavi Repalle: Electrical and Electronics Engineering, CVR College of Engineering, Hyderabad 501510, India
Pullacheri Sarala: Electrical and Electronics Engineering, Malla Reddy Engineering College, Maisammaguda, Secunderabad 500100, India
Lucian Mihet-Popa: Faculty of Information Technology, Engineering and Economics, Oestfold University College, 1757 Halden, Norway
Shashidhar Reddy Kotha: Electrical and Electronics Engineering, CVR College of Engineering, Hyderabad 501510, India
Nagalingam Rajeswaran: Electrical and Electronics Engineering, Malla Reddy Institute of Engineering and Technology, Maisammaguda, Secunderabad 500100, India

Energies, 2022, vol. 15, issue 13, 1-12

Abstract: The aging of PV cells reduces their electrical performance i.e., the parasitic parameters are introduced in the solar panel. The shunt resistance (R Sh ), series resistance (R S ), photo current (I Ph ), diode current (I d ), and diffusion constant (a 1 ) are known as parasitic or extraction parameters. Cracks and hotspots reduce the performance of PV cells and result in poor V–I characteristics. Certain tests are carried out over a long period of time to determine the quality of solar cells; for example, 1000 h of testing is comparable to 20 years of operation. The extraction of solar parameters is important for PV modules. The Tabu Search Optimization (TSO) algorithm is a robust meta-heuristic algorithm that was employed in this study for the extraction of parasitic parameters. Particle Swarm Optimization (PSO) and a Genetic lgorithm (GA), as well as other well-known optimization methods, were used to test the proposed method’s correctness. The other approaches included the lightning search algorithm (LSA), gravitational search algorithm (GSA), and pattern search (PS). It can be concluded that the TSO approach extracts all six parameters in a reasonably short period of time. The work presented in this paper was developed and analyzed using a MATLAB-Simulink software environment.

Keywords: synthetic data (SD); pattern search (PS); absolute error; optimization technique; solar cell (SC); tabu list (TL) (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 complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/13/4515/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/13/4515/ (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:15:y:2022:i:13:p:4515-:d:843906

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 ().