IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i18p4743-d412210.html
   My bibliography  Save this article

Dynamic Electro-Thermal PV Temperature and Power Output Prediction Model for Any PV Geometries in Free-Standing and BIPV Systems Operating under Any Environmental Conditions

Author

Listed:
  • Eleni Kaplani

    (Engineering, Faculty of Science, University of East Anglia, Norwich NR4 7TJ, UK)

  • Socrates Kaplanis

    (Renewable Energy Systems Lab, University of Peloponnese, 26334 Patra, Greece)

Abstract

PV temperature significantly affects the module’s power output and final system yield, and its accurate prediction can serve the forecasting of PV power output, smart grid operations, online PV diagnostics and dynamic predictive management of Building Integrated Photovoltaic (BIPV) systems. This paper presents a dynamic PV temperature prediction model based on transient Energy Balance Equations, incorporating theoretical expressions for all heat transfer processes, natural convection, forced convection, conduction and radiation exchanges between both module sides and the environment. The algorithmic approach predicts PV temperature at the centre of the cell, the back and the front glass cover with fast convergence and serves the PV power output prediction. The simulation model is robust, predicting PV temperature with high accuracy at any environmental conditions, PV inclination, orientation, wind speed and direction, and mounting configurations, free-standing and BIPV. These, alongside its theoretical basis, ensure the model’s wide applicability and clear advantage over existing PV temperature prediction models. The model is validated for a wide range of environmental conditions, PV geometries and mounting configurations with experimental data from a sun-tracking, a fixed angle PV and a BIPV system. The deviation between predicted and measured power output for the fixed-angle and the sun-tracking PV systems was estimated at −1.4% and 1.9%, respectively. The median of the temperature difference between predicted and measured values was as low as 0.5 °C for the sun-tracking system, and for all cases, the predicted temperature profiles were closely matching the measured profiles. The PV temperature and power output predicted by this model are compared to the results produced by other well-known PV temperature models, illustrating its high predictive capacity, accuracy and robustness.

Suggested Citation

  • Eleni Kaplani & Socrates Kaplanis, 2020. "Dynamic Electro-Thermal PV Temperature and Power Output Prediction Model for Any PV Geometries in Free-Standing and BIPV Systems Operating under Any Environmental Conditions," Energies, MDPI, vol. 13(18), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4743-:d:412210
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/18/4743/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/18/4743/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Socrates Kaplanis & Eleni Kaplani, 2018. "A New Dynamic Model to Predict Transient and Steady State PV Temperatures Taking into Account the Environmental Conditions," Energies, MDPI, vol. 12(1), pages 1-17, December.
    2. Waithiru Charles Lawrence Kamuyu & Jong Rok Lim & Chang Sub Won & Hyung Keun Ahn, 2018. "Prediction Model of Photovoltaic Module Temperature for Power Performance of Floating PVs," Energies, MDPI, vol. 11(2), pages 1-13, February.
    3. Mattei, M. & Notton, G. & Cristofari, C. & Muselli, M. & Poggi, P., 2006. "Calculation of the polycrystalline PV module temperature using a simple method of energy balance," Renewable Energy, Elsevier, vol. 31(4), pages 553-567.
    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. Socrates Kaplanis & Eleni Kaplani & John K. Kaldellis, 2023. "PV Temperature Prediction Incorporating the Effect of Humidity and Cooling Due to Seawater Flow and Evaporation on Modules Simulating Floating PV Conditions," Energies, MDPI, vol. 16(12), pages 1-19, June.
    2. Kaplanis, S. & Kaplani, E. & Kaldellis, J.K., 2022. "PV temperature and performance prediction in free-standing, BIPV and BAPV incorporating the effect of temperature and inclination on the heat transfer coefficients and the impact of wind, efficiency a," Renewable Energy, Elsevier, vol. 181(C), pages 235-249.

    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. Dong Eun Jung & Chanuk Lee & Kee Han Kim & Sung Lok Do, 2020. "Development of a Predictive Model for a Photovoltaic Module’s Surface Temperature," Energies, MDPI, vol. 13(15), pages 1-18, August.
    2. Socrates Kaplanis & Eleni Kaplani & John K. Kaldellis, 2023. "PV Temperature Prediction Incorporating the Effect of Humidity and Cooling Due to Seawater Flow and Evaporation on Modules Simulating Floating PV Conditions," Energies, MDPI, vol. 16(12), pages 1-19, June.
    3. Arsenio Barbón & Ángel Gutiérrez & Luis Bayón & Covadonga Bayón-Cueli & Javier Aparicio-Bermejo, 2023. "Economic Analysis of a Pumped Hydroelectric Storage-Integrated Floating PV System in the Day-Ahead Iberian Electricity Market," Energies, MDPI, vol. 16(4), pages 1-24, February.
    4. Socrates Kaplanis & Eleni Kaplani, 2018. "A New Dynamic Model to Predict Transient and Steady State PV Temperatures Taking into Account the Environmental Conditions," Energies, MDPI, vol. 12(1), pages 1-17, December.
    5. Rehman, Shafiqur & El-Amin, Ibrahim, 2012. "Performance evaluation of an off-grid photovoltaic system in Saudi Arabia," Energy, Elsevier, vol. 46(1), pages 451-458.
    6. Meng, Zhuo & Zhao, Yiman & Tang, Shiqing & Sun, Yize, 2020. "An efficient datasheet-based parameters extraction method for two-diode photovoltaic cell and cells model," Renewable Energy, Elsevier, vol. 153(C), pages 1174-1182.
    7. Mayer, Martin János & Yang, Dazhi & Szintai, Balázs, 2023. "Comparing global and regional downscaled NWP models for irradiance and photovoltaic power forecasting: ECMWF versus AROME," Applied Energy, Elsevier, vol. 352(C).
    8. Daniel Matulić & Željko Andabaka & Sanja Radman & Goran Fruk & Josip Leto & Jakša Rošin & Mirta Rastija & Ivana Varga & Tea Tomljanović & Hrvoje Čeprnja & Marko Karoglan, 2023. "Agrivoltaics and Aquavoltaics: Potential of Solar Energy Use in Agriculture and Freshwater Aquaculture in Croatia," Agriculture, MDPI, vol. 13(7), pages 1-26, July.
    9. Amirhossein Fathi & Masoomeh Bararzadeh Ledari & Yadollah Saboohi, 2021. "Evaluation of Optimal Occasional Tilt on Photovoltaic Power Plant Energy Efficiency and Land Use Requirements, Iran," Sustainability, MDPI, vol. 13(18), pages 1-20, September.
    10. Rustemli, Sabir & Dincer, Furkan & Unal, Emin & Karaaslan, Muharrem & Sabah, Cumali, 2013. "The analysis on sun tracking and cooling systems for photovoltaic panels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 598-603.
    11. Kaplanis, S. & Kaplani, E. & Kaldellis, J.K., 2022. "PV temperature and performance prediction in free-standing, BIPV and BAPV incorporating the effect of temperature and inclination on the heat transfer coefficients and the impact of wind, efficiency a," Renewable Energy, Elsevier, vol. 181(C), pages 235-249.
    12. Thopil, George Alex & Sachse, Christiaan Eddie & Lalk, Jörg & Thopil, Miriam Sara, 2020. "Techno-economic performance comparison of crystalline and thin film PV panels under varying meteorological conditions: A high solar resource southern hemisphere case," Applied Energy, Elsevier, vol. 275(C).
    13. 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.
    14. Rahaman, Md Atiqur & Chambers, Terrence L. & Fekih, Afef & Wiecheteck, Giovana & Carranza, Gabriel & Possetti, Gustavo Rafael Collere, 2023. "Floating photovoltaic module temperature estimation: Modeling and comparison," Renewable Energy, Elsevier, vol. 208(C), pages 162-180.
    15. Chikh, Madjid & Berkane, Smain & Mahrane, Achour & Sellami, Rabah & Yassaa, Noureddine, 2021. "Performance assessment of a 400 kWp multi- technology photovoltaic grid-connected pilot plant in arid region of Algeria," Renewable Energy, Elsevier, vol. 172(C), pages 488-501.
    16. Klamka, Jonas & Wolf, André & Ehrlich, Lars G., 2020. "Photovoltaic self-consumption after the support period: Will it pay off in a cross-sector perspective?," Renewable Energy, Elsevier, vol. 147(P1), pages 2374-2386.
    17. Deveci, Muhammet & Pamucar, Dragan & Oguz, Elif, 2022. "Floating photovoltaic site selection using fuzzy rough numbers based LAAW and RAFSI model," Applied Energy, Elsevier, vol. 324(C).
    18. Kane, Aarti & Verma, Vishal & Singh, Bhim, 2017. "Optimization of thermoelectric cooling technology for an active cooling of photovoltaic panel," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1295-1305.
    19. Mäki, Anssi & Valkealahti, Seppo, 2014. "Differentiation of multiple maximum power points of partially shaded photovoltaic power generators," Renewable Energy, Elsevier, vol. 71(C), pages 89-99.
    20. Trinuruk, Piyatida & Sorapipatana, Chumnong & Chenvidhya, Dhirayut, 2009. "Estimating operating cell temperature of BIPV modules in Thailand," Renewable Energy, Elsevier, vol. 34(11), pages 2515-2523.

    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:13:y:2020:i:18:p:4743-:d:412210. 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.