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

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...

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Bibliographic Details
Published in:Renewable energy 2020-06, Vol.152, p.1186-1191
Main Author: Schuster, Christian Stefano
Format: Article
Language:English
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Summary: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. [Display omitted] •Angle-resolved insolation profiles are invariant to climate/weather changes.•Angle-resolved insolation profiles are site-independent for latitude-tilted panels.•Solar PV optimal tilt angles are compared for four distinct climatic zones on Earth.•All insolation levels include cloud cover periods and other atmospheric dynamics.•Solar spectra modelled at high temporal and spectral resolution via satellite data.
ISSN:0960-1481
1879-0682
DOI:10.1016/j.renene.2020.01.076