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The quest for the optimum angular-tilt of terrestrial solar panels or their angle-resolved annual insolation

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  • Schuster, Christian Stefano

Abstract

Although solar energy is the fastest growing power technology, terrestrial solar panels typically fall behind their performance ratings established under standardised test-conditions. In particular, the angular-tilt of a panel can greatly affect its overall performance. Many studies thus aim to find the optimum tilt that maximises the annual insolation level. However, no widespread consensus has so far been found, partly because of different model assumptions applied. Here, a technique is proposed to use actual, historical solar spectra for the rigorous assessment of a panel’s tilt at a specific site. By combining multiple, free-accessible satellite-retrieved data products, the total all-sky insolation levels are tracked with a minutely changing global (hemispherical) solar spectrum over many years. While time-resolved annual insolation profiles can considerably vary among each other, the solar angle-resolved profile turns out to be robust to climatic conditions and is even site-independent for latitude-tilted panels. These findings can potentially unlock innovative yield optimisation methods.

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  • Schuster, Christian Stefano, 2020. "The quest for the optimum angular-tilt of terrestrial solar panels or their angle-resolved annual insolation," Renewable Energy, Elsevier, vol. 152(C), pages 1186-1191.
    • Handle: RePEc:eee:renene:v:152:y:2020:i:c:p:1186-1191
    DOI: 10.1016/j.renene.2020.01.076
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    References listed on IDEAS

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    Cited by:

    1. Oh, Myeongchan & Kim, Jin-Young & Kim, Boyoung & Yun, Chang-Yeol & Kim, Chang Ki & Kang, Yong-Heack & Kim, Hyun-Goo, 2021. "Tolerance angle concept and formula for practical optimal orientation of photovoltaic panels," Renewable Energy, Elsevier, vol. 167(C), pages 384-394.
    2. Liu, Yujun & Yao, Ling & Jiang, Hou & Lu, Ning & Qin, Jun & Liu, Tang & Zhou, Chenghu, 2022. "Spatial estimation of the optimum PV tilt angles in China by incorporating ground with satellite data," Renewable Energy, Elsevier, vol. 189(C), pages 1249-1258.
    3. Ramez Abdallah & Emad Natsheh & Adel Juaidi & Sufyan Samara & Francisco Manzano-Agugliaro, 2020. "A Multi-Level World Comprehensive Neural Network Model for Maximum Annual Solar Irradiation on a Flat Surface," Energies, MDPI, vol. 13(23), pages 1-31, December.
    4. Schuster, Christian Stefano & Koc, Mehmet & Yerci, Selcuk, 2022. "Analytic modelling of multi-junction solar cells via multi-diodes," Renewable Energy, Elsevier, vol. 184(C), pages 1033-1042.
    5. Wang, Tiantian & Wang, Yanhua & Wang, Ke & Fu, Sha & Ding, Li, 2024. "Five-dimensional assessment of China's centralized and distributed photovoltaic potential: From solar irradiation to CO2 mitigation," Applied Energy, Elsevier, vol. 356(C).
    6. Chen, Xiaomeng & Wang, Yang & Yang, Xudong, 2023. "New biaxial approach to evaluate the optical performance of evacuated tube solar thermal collector," Energy, Elsevier, vol. 271(C).
    7. Xu, Luting & Long, Enshen & Wei, Jincheng & Cheng, Zhu & Zheng, Hanjie, 2021. "A new approach to determine the optimum tilt angle and orientation of solar collectors in mountainous areas with high altitude," Energy, Elsevier, vol. 237(C).
    8. Schuster, Christian Stefano, 2020. "Analytical framework for the assessment and modelling of multi-junction solar cells in the outdoors," Renewable Energy, Elsevier, vol. 152(C), pages 1367-1379.

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