Bright-Sun: A globally applicable 1-min irradiance clear-sky detection model

• Published in: Renewable & sustainable energy reviews Vol. 121; p. 109706
• Main Authors: Bright, Jamie M., Sun, Xixi, Gueymard, Christian A., Acord, Brendan, Wang, Peng, Engerer, Nicholas A.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-04-2020
• Subjects: Bright-Sun CSD; Clear-sky; Clear-sky detection; Cloudless sky; Irradiance; Clear-sky; Bright-Sun CSD; Irradiance; Clear-sky detection; Cloudless sky
• ISSN: 1364-0321; 1879-0690
• DOI: 10.1016/j.rser.2020.109706

Clear-sky detection (CSD) is a crucial process in numerous solar energy applications. Many CSD models have been proposed over the years, though model performance is generally found unsatisfactory for worldwide use. We demonstrate this qualitatively on 22 CSD models at five climatologically-diverse radiometric stations; all exhibit one or more limitations: (1) unreliability at high zenith; (2) unrealistic “clear” periods immediately before or after cloudy conditions; (3) relaxed (short-term false positives); (4) over-relaxed during clear conditions (longer-term false positives); (5) conservative (short-term false negatives); and (6) over-conservative during clear conditions (longer-term false negatives).
A new globally applicable CSD methodology is proposed for a posteriori detection of apparent “cloudless sky” conditions on 1-min irradiance time series, named the Bright-Sun model. This new tool requires measured global horizontal irradiance (GHI) and diffuse horizontal irradiance (DIF), and consists of three stages: (1) clear-sky irradiance optimisation, (2) tri-component CSD analysis with the newly derived Modified-Reno method, and (3) a cascading durational filters to determine periods of apparent cloudless sky. Through qualitative evaluation and exploring sensitivity to clear-sky model selection, the Bright-Sun model does not suffer any of the aforementioned limitations at any of the five stations, despite their distinctive climates. Due to the significant influence of bright or dark clouds on DIF, which have much lower impact on GHI, the new model also exhibits extra discretionary power by including analysis on DIF and can thus identify apparently clear periods with zero or near-zero cloudiness.
The Bright-Sun CSD model is coded in Matlab®and freely available (future releases in R and Python are anticipated). A script is attached as supplementary material in the original form. For a supported and version controlled release of the Bright-Sun model, as well as other CSD models mentioned within this document, the reader can refer to the CSD Library at https://jamiembright.github.io/csd-library/.
•A new clear-sky detection (CSD) methodology is presented for worldwide usage.•It is in 3 stages: clear-sky optimisation, tri-component analysis, duration filters.•The Reno CSD method is re-parameterised and modified for normalised CSD criteria.•The Bright-Sun model qualitatively resolves pre-existing issues in existing methods.•The Bright-Sun model performs well over 5 climates, outperforming older CSD models.