Modeling and Simulation of Silicon Solar Cells under Low Concentration Conditions
Gulbakhar Dosymbetova,
Saad Mekhilef,
Ahmet Saymbetov (),
Madiyar Nurgaliyev,
Ainur Kapparova,
Sergey Manakov,
Sayat Orynbassar,
Nurzhigit Kuttybay,
Yeldos Svanbayev,
Isroil Yuldoshev,
Batyrbek Zholamanov and
Nursultan Koshkarbay
Additional contact information
Gulbakhar Dosymbetova: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Saad Mekhilef: Power Electronics and Renewable Energy Research Laboratory, Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
Ahmet Saymbetov: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Madiyar Nurgaliyev: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Ainur Kapparova: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Sergey Manakov: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Sayat Orynbassar: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Nurzhigit Kuttybay: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Yeldos Svanbayev: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Isroil Yuldoshev: Department “Alternative Energy Sources”, Tashkent State Technical University Named after Islam Karimov, University Street 2, Tashkent 700095, Uzbekistan
Batyrbek Zholamanov: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Nursultan Koshkarbay: Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty 050040, Kazakhstan
Energies, 2022, vol. 15, issue 24, 1-17
Abstract:
Today’s research on concentrated photovoltaic (CPV) cells focuses on creating multi-junction semiconductor solar cells capable of withstanding high temperatures without losing their properties. This paper investigated silicon low concentrated photovoltaic (LCPV) devices using Fresnel lenses. The parameters of the silicon CPV cell were measured to simulate its operation based on a single-diode model with four and five parameters. The most optimal position of the Fresnel lens relative to the solar cell was shown, and the dependence of the CPV efficiency on the concentration ratio, incident solar power, and temperature was studied. Experiments on heating of a solar cell were conducted to build a model of heating of a solar cell under different solar radiation based on machine learning. Additionally, a cooling system was developed, and experiments were conducted for one LCPV cell. The resulting LCPV model was used to predict electrical power output and temperature change pattern using clear day data. Results of modeling show increase in generated energy by 27% compared with non-concentrated solar cells. Cooling system energy consumption was simulated, and the optimum cooling regime was determined. The proposed LCPV system can be used as a hybrid heat and electricity source, increase power generation, and does not require new solar cell production technologies.
Keywords: low concentrated photovoltaic cells (LCPV); Fresnel lens; machine learning; cooling system; single-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:
Downloads: (external link)
https://www.mdpi.com/1996-1073/15/24/9404/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/24/9404/ (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:24:p:9404-:d:1001187
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 ().