AI Article Synopsis

  • Analysis of daily solar irradiation variability is crucial for effective energy resource planning and management, as it’s affected by factors like cloudiness and terrain.
  • A study conducted on solar irradiance data from La Reunion Island during 2013-2015 revealed high complexity in half-day solar irradiation patterns, leading to classification into three distinct groups based on trade wind influences.
  • The research introduces a measure called Kolmogorov time, which helps quantify how randomness impacts the predictability of solar irradiation over time.

Article Abstract

Analysis of daily solar irradiation variability and predictability in space and time is important for energy resources planning, development, and management. The natural variability of solar irradiation is being complicated by atmospheric conditions (in particular cloudiness) and orography, which introduce additional complexity into the phenomenological records. To address this question for daily solar irradiation data recorded during the years 2013, 2014 and 2015 at 11 stations measuring solar irradiance on La Reunion French tropical Indian Ocean Island, we use a set of novel quantitative tools: Kolmogorov complexity () with its derivative associated measures and Hamming distance () and their combination to assess complexity and corresponding predictability. We find that all half-day (from sunrise to sunset) solar irradiation series exhibit high complexity. However, all of them can be classified into three groups strongly influenced by trade winds that circulate in a "flow around" regime: the windward side (trade winds slow down), the leeward side (diurnal thermally-induced circulations dominate) and the coast parallel to trade winds (winds are accelerated due to Venturi effect). We introduce Kolmogorov time () that quantifies the time span beyond which randomness significantly influences predictability.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513096PMC
http://dx.doi.org/10.3390/e20080570DOI Listing

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