Suppr超能文献

结合柯尔莫哥洛夫测度和汉明距离对留尼汪岛(法国)太阳辐射时间序列的复杂性和可预测性进行分析

Analysis of Solar Irradiation Time Series Complexity and Predictability by Combining Kolmogorov Measures and Hamming Distance for La Reunion (France).

作者信息

Mihailović Dragutin T, Bessafi Miloud, Marković Sara, Arsenić Ilija, Malinović-Milićević Slavica, Jeanty Patrick, Delsaut Mathieu, Chabriat Jean-Pierre, Drešković Nusret, Mihailović Anja

机构信息

Faculty of Agriculture, University of Novi Sad, Dositej Obradovic Sq. 8, 21000 Novi Sad, Serbia.

Faculty of Sciences and Technology, University of La Réunion, Laboratoire d'Energétique, d'Electronique et Procédés, 15 Avenue René Cassin, Sainte-Clotilde, 97715 La Réunion, France.

出版信息

Entropy (Basel). 2018 Aug 1;20(8):570. doi: 10.3390/e20080570.

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.

摘要

分析太阳辐照在空间和时间上的日变化及可预测性,对于能源资源的规划、开发和管理至关重要。太阳辐照的自然变化因大气条件(特别是云量)和地形而变得复杂,这给现象学记录增添了额外的复杂性。为解决2013年、2014年和2015年期间在法属印度洋留尼汪岛的11个测量太阳辐照度的站点记录的日太阳辐照数据的这一问题,我们使用了一套新颖的定量工具:具有其相关衍生度量的柯尔莫哥洛夫复杂度()和汉明距离()及其组合,以评估复杂性和相应的可预测性。我们发现,所有半日(从日出到日落)太阳辐照序列都表现出高复杂性。然而,所有这些序列都可分为三组,受以“绕流”模式环流的信风强烈影响:迎风面(信风减速)、背风面(昼夜热致环流占主导)以及与信风平行的海岸(由于文丘里效应风加速)。我们引入了柯尔莫哥洛夫时间(),它量化了随机性对可预测性产生显著影响的时间跨度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/140f/7513096/06e45332eb25/entropy-20-00570-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验