Modeling of energy gain in bifacial vertical PV fences

Aasim A.  Azooz; Zeyad T.  Ali

doi:10.59400/esc1957

Modeling of energy gain in bifacial vertical PV fences

Aasim A. Azooz Department of Physics, College of Science, Mosul University, Mosul 41002, Iraq
Zeyad T. Ali Department of Electrical engineering and Electronics, University of Liverpool, Liverpool L3 5TR, UK

Article ID: 1957

DOI: https://doi.org/10.59400/esc1957

Keywords: PV-panels; PV fences; vertical installation; fences PV energy

Abstract

A quantitative model-based analysis was conducted to estimate the percentage output energy ratio of vertically installed bifacial PV modules in fences, cattle barriers, and roadsides compared to the output energy of two types of monofacial PV installations. The first comparison is between the output of the vertical bifacial PV fence and the output of the same fence furnished with vertically installed monofacial PV modules. The second comparison is between the output of the vertical bifacial fence and the output of south-facing monofacial PV modules installed at the optimal inclination angle for the particular latitude. The results show that bifacial fences can produce net yearly energy outputs up to 80% higher than those of monofacial PV modules. Additionally, vertical bifacial PV fences produce only a few percent lower energy compared to optimally installed monofacial PV modules. A MATLAB software program was written to calculate the gain of fences of any geometry, and it has been made freely available. Examples of gain results for a few such geometries are presented.

References

[1]Becquerel M. Mémoire sur les effets électriques produits sous l'influence des rayons solaires. Comptes rendus hebdomadaires des séances de l'Académie des sciences. 1839; 9: 561-567.

[2]Starowicz A, Rusanowska P, Zieliński M. Photovoltaic cell—the history of invention—review. Polityka Energetyczna—Energy Policy Journal. 2023; 26(1): 169–180. doi: 10.33223/epj/161290

[3]IEA. In 2023, solar PV alone accounted for three-quarters of renewable capacity additions worldwide. Available online: https://www.iea.org/energysystem/renewables/solar-pv (accessed on 10 June 2024).

[4]IEA. Executive Summary. Available online: https://iea-pvps.org/snapshot-reports/snapshot-2023/ (accessed on 12 June 2024).

[5]IEA. Renewable Energy Market Update Outlook for 2023 and 2024. Available online: https://www.iea.org/reports/renewable-energy-market-update-june-2023/executive-summary (accessed on 13 June 2024).

[6]Hezel R. Novel applications of bifacial solar cells. Progress in Photovoltaics: Research and Applications. 2003; 11(8): 549–556. doi: 10.1002/pip.510

[7]Libal J, Kopecek R. Bifacial Photovoltaics: Technology, Applications and Economics. Institution of Engineering and Technology; 2018. doi: 10.1049/pbpo107e

[8]Matarneh G A, Al-Rawajfeh M A, Gomaa M R. Comparison review between monofacial and bifacial solar modules. Technology audit and production reserves. 2022; 6(1(68)): 24–29. doi: 10.15587/2706-5448.2022.268955

[9]Braga D S, Kazmerski L L, Cassini D A, et al. Performance of bifacial PV modules under different operating conditions in the State of Minas Gerais, Brazil. Renewable Energy and Environmental Sustainability. 2023; 8: 23. doi: 10.1051/rees/2023021

[10]Chunduri S K, Schmela M. Bifacial Solar Module Technology 2018 Edition. Available online: https://www.researchgate.net/publication/354813723_Bifacial_Solar_Module_Technology_2018_Edition_-_Getting_Ready_For_Much_Higher_Yields_With_Bifacial_Modules?channel=doi&linkId=614dd2fdf8c9c51a8aeec8ab&showFulltext=true (accessed on 13 June 2024).

[11]Lorenzo E. On the historical origins of bifacial PV modelling. Solar Energy. 2021; 218: 587–595. doi: 10.1016/j.solener.2021.03.006

[12]Eguren J, Martínez-Moreno F, Merodio P, et al. First bifacial PV modules early 1983. Solar Energy. 2022; 243: 327–335. doi: 10.1016/j.solener.2022.08.002

[13]RenewSys. Bifacial Solar Cells. Available online: https://www.renewsysworld.com/post/bifacial-solar-cells (accessed on 11 July 2024).

[14]Alternergy. Bifacial solar panels: What are they and are they worth it? Available online: https://www.alternergy.co.uk/blog/post/bifacial-solar-panels-what-are-they (accessed on 2 July 2024).

[15]Issaq S Z, Talal S K, Azooz A A. Empirical modeling of optimum tilt angle for flat solar collectors and PV panels. Environmental Science and Pollution Research. 2023; 30(33): 81250–81266. doi: 10.1007/s11356-023-28142-3

[16]Langels H, Gannedahl F. BiFacial PV Systems: A technological and financial comparison between BiFacial and standard PV panels. Available online: https://www.semanticscholar.org/paper/BiFacial-PV-Systems-%3A-A-technological-and-financial-Langels-Gannedahl/05e95ec78d3f5676c4307713c3088d84af0db6bb (accessed on 13 June 2024).

[17]Kumbaroğlu G S, Çamlibel M E, Avcı C. Techno-economic comparison of bifacial vs monofacial solar panels. Engineering Structures and Technologies. 2021; 13(1): 7–18.

[18]HOMER. Published Solar Data.HOMER Energy. Available online: https://homerenergy.com/products/pro/docs/3.15/index.html (accessed on 12 July 2024).

[19]Orgill J, Hollands K. Correlation equation for hourly diffuse radiation on a horizontal surface. Solar energy. 1977; 19(4): 357–359.

[20]Duffie JA, Beckman W A. Solar engineering of thermal processes. Wiley New York; 1980.

[21]Widén J, Munkhammar J. Solar Radiation Theory. Uppsala University; 2019.

[22]MOSAiC. Quick Bite: Albedo Comparison. University of Colorado Boulder. Available online: https://mosaic.colorado.edu/quick-bite-albedo-comparison (accessed on 3 August 2024).

[23]Guerrero-Lemus R, Vega R, Kim T, et al. Bifacial solar photovoltaics—A technology review. Renewable and Sustainable Energy Reviews. 2016; 60: 1533–1549. doi: 10.1016/j.rser.2016.03.041

[24]Azooz AA. Software for calculating energy gain when using bifacial PV” MATLAB file exchange library. Available online: https://www.mathworks.com/matlabcentral/fileexchange/171169-software-for-calculating-energy-gain-when-using-bifacial-pv (accessed on 13 June 2024).

[25]Castillo-Aguilella J E, Hauser P S. Multi-Variable Bifacial Photovoltaic Module Test Results and Best-Fit Annual Bifacial Energy Yield Model. IEEE Access. 2016; 4: 498–506. doi: 10.1109/access.2016.2518399

[26]Du H, Hao G, Li H, et al. Analysis of annual bifacial gain in energy and annual energy yield of bifacial modules at low latitudes. International Journal of Green Energy. 2021; 18(15): 1632–1644. doi: 10.1080/15435075.2021.1930000

[27]Hayibo K S, Petsiuk A, Mayville P, et al. Monofacial vs bifacial solar photovoltaic systems in snowy environments. Renewable Energy. 2022; 193: 657–668. doi: 10.1016/j.renene.2022.05.050

[28]Aksoy M H, Çalik M K. Çift Yüzlü Fotovoltaik Panellerin Farklı Zemin Koşullarında Performansının İncelenmesi. Konya Journal of Engineering Sciences. 2022; 10(3): 704–718. doi: 10.36306/konjes.1116729

[29]Bifacial vs. Monofacial Solar Panels: Which One is Right for Your Solar System? Available online: https://rocksolar.ca/blogs/news/bifacial-vs-monofacial-solar-panels-which-one-is-right-for-your-solar-system (accessed on 13 June 2024).

[30]Heltsley K. Bifacial Solar Panels vs Monocrystalline Solar Panels. Available online: https://www.itekenergy.com/solar-panels/bifacial-solar-panels-vs-monocrystalline-solar-panels/ (accessed on 13 June 2024).

[31]Tan D. Monofacial vs. Bifacial Solar Panels: Which is Best for Your Solar Setup? Available online: https://directsolarpower.com/blogs/learning-center/monofacial-vs-bifacial-solar-panels-which-is-best-for-your-solar-setup (accessed on 13 June 2024).

Published

2025-01-03

How to Cite

Azooz, A. A., & Ali, Z. T. (2025). Modeling of energy gain in bifacial vertical PV fences. Energy Storage and Conversion, 3(1), 1957. https://doi.org/10.59400/esc1957

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