IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i11p3917-d824304.html
   My bibliography  Save this article

Comparative Analysis of Power Output, Fill Factor, and Efficiency at Fixed and Variable Tilt Angles for Polycrystalline and Monocrystalline Photovoltaic Panels—The Case of Sukkur IBA University

Author

Listed:
  • Lyu-Guang Hua

    (Power China Huadong Engineering Co., Ltd., Hangzhou 311122, China)

  • Qasir Ali Memon

    (Department of Electrical Engineering, Sukkur IBA University, Sukkur 65200, Pakistan)

  • Muhammad Fawad Shaikh

    (Department of Electrical Engineering, Sukkur IBA University, Sukkur 65200, Pakistan)

  • Shoaib Ahmed Shaikh

    (Department of Electrical Engineering, Sukkur IBA University, Sukkur 65200, Pakistan)

  • Rehan Ali Rahimoon

    (Department of Electrical Engineering, Sukkur IBA University, Sukkur 65200, Pakistan)

  • Syed Hadi Hussain Shah

    (Department of Electrical and Computer Engineering, Mohammad Ali Jinnah University, Karachi 75400, Pakistan)

  • Abdul Qadir

    (Department of Electrical Engineering, Sukkur IBA University, Sukkur 65200, Pakistan)

Abstract

Photovoltaic technology mainly uses beam, diffused, and reflected solar radiation to produce power. To increase the photovoltaic power output, the surface of the solar panel must be at the optimal tilt angle. In this paper, a numerical study is carried out to investigate the optimal tilt angle for a 1 MW PV system installed at Sukkur IBA University (latitude = 27.7268° N, longitude = 68.8191° E). Moreover, power output, efficiency, and fill factor are calculated for polycrystalline and monocrystalline solar panels. Results obtained at different tilt angles are used to compare the solar gain from photovoltaic modules installed at the university. In conclusion, an optimal tilt angle is decided for both polycrystalline and monocrystalline solar panels used at Sukkur IBA University. It was found that the optimal tilt angle for the installed 1 MW systems is 29.5 degrees.

Suggested Citation

  • Lyu-Guang Hua & Qasir Ali Memon & Muhammad Fawad Shaikh & Shoaib Ahmed Shaikh & Rehan Ali Rahimoon & Syed Hadi Hussain Shah & Abdul Qadir, 2022. "Comparative Analysis of Power Output, Fill Factor, and Efficiency at Fixed and Variable Tilt Angles for Polycrystalline and Monocrystalline Photovoltaic Panels—The Case of Sukkur IBA University," Energies, MDPI, vol. 15(11), pages 1-16, May.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:3917-:d:824304
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/11/3917/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/11/3917/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhou, Wei & Yang, Hongxing & Fang, Zhaohong, 2007. "A novel model for photovoltaic array performance prediction," Applied Energy, Elsevier, vol. 84(12), pages 1187-1198, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kyoik Choi & Jangwon Suh, 2023. "Fault Detection and Power Loss Assessment for Rooftop Photovoltaics Installed in a University Campus, by Use of UAV-Based Infrared Thermography," Energies, MDPI, vol. 16(11), pages 1-16, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rawat, Rahul & Kaushik, S.C. & Lamba, Ravita, 2016. "A review on modeling, design methodology and size optimization of photovoltaic based water pumping, standalone and grid connected system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1506-1519.
    2. Markus Mirz & Lukas Razik & Jan Dinkelbach & Halil Alper Tokel & Gholamreza Alirezaei & Rudolf Mathar & Antonello Monti, 2018. "A Cosimulation Architecture for Power System, Communication, and Market in the Smart Grid," Complexity, Hindawi, vol. 2018, pages 1-12, February.
    3. Yadav, Pankaj & Tripathi, Brijesh & Rathod, Siddharth & Kumar, Manoj, 2013. "Real-time analysis of low-concentration photovoltaic systems: A review towards development of sustainable energy technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 812-823.
    4. Mahesh Vinayak Hadole & Kamlesh Narayan Tiwari & Prabodh Bajpai, 2021. "Energy generation and flow rate prediction of photovoltaic water pumping system for irrigation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 6722-6733, May.
    5. Edalati, Saeed & Ameri, Mehran & Iranmanesh, Masoud, 2015. "Comparative performance investigation of mono- and poly-crystalline silicon photovoltaic modules for use in grid-connected photovoltaic systems in dry climates," Applied Energy, Elsevier, vol. 160(C), pages 255-265.
    6. Wang, Meng & Peng, Jinqing & Luo, Yimo & Shen, Zhicheng & Yang, Hongxing, 2021. "Comparison of different simplistic prediction models for forecasting PV power output: Assessment with experimental measurements," Energy, Elsevier, vol. 224(C).
    7. Silvestre, S. & Boronat, A. & Chouder, A., 2009. "Study of bypass diodes configuration on PV modules," Applied Energy, Elsevier, vol. 86(9), pages 1632-1640, September.
    8. Nader Anani & Haider Ibrahim, 2020. "Adjusting the Single-Diode Model Parameters of a Photovoltaic Module with Irradiance and Temperature," Energies, MDPI, vol. 13(12), pages 1-17, June.
    9. Bonanno, F. & Capizzi, G. & Graditi, G. & Napoli, C. & Tina, G.M., 2012. "A radial basis function neural network based approach for the electrical characteristics estimation of a photovoltaic module," Applied Energy, Elsevier, vol. 97(C), pages 956-961.
    10. Ma, Zhenjun & Wang, Shengwei, 2009. "Building energy research in Hong Kong: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1870-1883, October.
    11. Sarah O’Connell & Marcus Martin Keane, 2021. "Development of a Framework for Activation of Aggregator Led Flexibility," Energies, MDPI, vol. 14(16), pages 1-15, August.
    12. Lo Brano, Valerio & Ciulla, Giuseppina, 2013. "An efficient analytical approach for obtaining a five parameters model of photovoltaic modules using only reference data," Applied Energy, Elsevier, vol. 111(C), pages 894-903.
    13. Koussa, M. & Cheknane, A. & Hadji, S. & Haddadi, M. & Noureddine, S., 2011. "Measured and modelled improvement in solar energy yield from flat plate photovoltaic systems utilizing different tracking systems and under a range of environmental conditions," Applied Energy, Elsevier, vol. 88(5), pages 1756-1771, May.
    14. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "Solar photovoltaic system modeling and performance prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 304-315.
    15. Christil Pasion & Torrey Wagner & Clay Koschnick & Steven Schuldt & Jada Williams & Kevin Hallinan, 2020. "Machine Learning Modeling of Horizontal Photovoltaics Using Weather and Location Data," Energies, MDPI, vol. 13(10), pages 1-14, May.
    16. Mellit, Adel & Kalogirou, Soteris A., 2011. "ANFIS-based modelling for photovoltaic power supply system: A case study," Renewable Energy, Elsevier, vol. 36(1), pages 250-258.
    17. Sonja Kolen & Stefan Dähling & Timo Isermann & Antonello Monti, 2018. "Enabling the Analysis of Emergent Behavior in Future Electrical Distribution Systems Using Agent-Based Modeling and Simulation," Complexity, Hindawi, vol. 2018, pages 1-16, February.
    18. Papaioannou, Ioulia T. & Purvins, Arturs, 2012. "Mathematical and graphical approach for maximum power point modelling," Applied Energy, Elsevier, vol. 91(1), pages 59-66.
    19. de la Parra, I. & Muñoz, M. & Lorenzo, E. & García, M. & Marcos, J. & Martínez-Moreno, F., 2017. "PV performance modelling: A review in the light of quality assurance for large PV plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 780-797.
    20. Blaifi, Sid-ali & Moulahoum, Samir & Taghezouit, Bilal & Saim, Abdelhakim, 2019. "An enhanced dynamic modeling of PV module using Levenberg-Marquardt algorithm," Renewable Energy, Elsevier, vol. 135(C), pages 745-760.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:3917-:d:824304. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.