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A global annual optimum tilt angle model for photovoltaic generation to use in the absence of local meteorological data

Author

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  • Nicolás-Martín, Carolina
  • Santos-Martín, David
  • Chinchilla-Sánchez, Mónica
  • Lemon, Scott

Abstract

This manuscript proposes a series of global models to estimate optimum annual tilt angle (βopt) as a function of local variables (latitude, diffuse fraction and albedo) based on the hourly irradiance data of 14,468 sites spread across the globe from the One Building database. As a result, these models can be used for any location in the absence of local meteorological data. First, a polynomial regression model, applicable worldwide, is proposed to estimate βopt as a function of latitude. This model fits the global data considered with a 2% RMSE error. Average energy losses are estimated to be 1% for a 10° variation from βopt. A variation of 40° with respect to βopt, implies a 12–18% energy loss depending on latitude. In addition, if only latitude is considered to estimate βopt, different expressions should be used for latitudes >50° depending on the hemisphere. These variations are a result of the influence of diffuse irradiance on βopt, due to the fact that sites with higher amounts of diffuse irradiance have a lower βopt. Secondly, a polynomial surface regression model to estimate βopt as a function of latitude and the annual diffuse fraction is proposed improving the results, reaching a 0.7% RMSE error. Thirdly, a simplified polynomial surface regression model to estimate βopt as a function of latitude and albedo (without the influence of the diffuse fraction) is proposed, and finally a model gathering all three variables under study (latitude, annual diffuse fraction and albedo) to calculate the optimum tilt angle is presented.

Suggested Citation

  • Nicolás-Martín, Carolina & Santos-Martín, David & Chinchilla-Sánchez, Mónica & Lemon, Scott, 2020. "A global annual optimum tilt angle model for photovoltaic generation to use in the absence of local meteorological data," Renewable Energy, Elsevier, vol. 161(C), pages 722-735.
    • Handle: RePEc:eee:renene:v:161:y:2020:i:c:p:722-735
    DOI: 10.1016/j.renene.2020.07.098
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    References listed on IDEAS

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    Cited by:

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    2. Arsenio Barbón & Luis Bayón & Guzmán Díaz & Carlos A. Silva, 2022. "Investigation of the Effect of Albedo in Photovoltaic Systems for Urban Applications: Case Study for Spain," Energies, MDPI, vol. 15(21), pages 1-20, October.
    3. Dragos Machidon & Marcel Istrate, 2023. "Tilt Angle Adjustment for Incident Solar Energy Increase: A Case Study for Europe," Sustainability, MDPI, vol. 15(8), pages 1-12, April.
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    5. Ruan, Tianqi & Wang, Fuxing & Topel, Monika & Laumert, Björn & Wang, Wujun, 2024. "A new optimal PV installation angle model in high-latitude cold regions based on historical weather big data," Applied Energy, Elsevier, vol. 359(C).
    6. Ioannis-Panagiotis Raptis & Anna Moustaka & Panagiotis Kosmopoulos & Stelios Kazadzis, 2022. "Selecting Surface Inclination for Maximum Solar Power," Energies, MDPI, vol. 15(13), pages 1-16, June.

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