Analysis of intra-day solar irradiance variability in different Brazilian climate zones

• Published in: Solar energy Vol. 167; pp. 210 - 219
• Main Authors: Luiz, Eduardo Weide, Martins, Fernando Ramos, Gonçalves, André Rodrigues, Pereira, Enio Bueno
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.06.2018; Pergamon Press Inc
• Subjects: Celestial bodies; Climate; Cloud cover; Clouds; Correlation analysis; Effective cloud cover; Electricity distribution; Electricity generation; Energy; Ground-based observation; Irradiance; Satellite data; Satellite imagery; Satellite observation; Solar energy; Solar variability; Spatial discrimination; Temperature; Variability; Brazil; Effective cloud cover; Satellite data; Solar variability
• ISSN: 0038-092X; 1471-1257
• DOI: 10.1016/j.solener.2018.04.005

•The driest location analyzed present the highest variability for timescales smaller that 20-min.•A relationship between ground-based irradiance variability and cloud cover satellite variability is found.•For the same timescale (30-min) the relationship is well-correlated.•A simple methodology for solar irradiance variability analysis is presented. One of the main barriers to increasing the solar energy share is its intermittency. Solar energy’s large variability in different timescales is driven by natural solar astronomical cycles and weather. Ground-based measurements are important for evaluating variability at high temporal resolutions, but they are only representative of small areas close to the measurement sites. Satellite observations come as an alternative to analysis over large areas. However, they have coarse temporal and spatial resolutions. In our study, we first evaluated the variability in different time steps, using one-year of 1-min resolution ground-based irradiance measured at three sites located in different Brazilian climate regimes. The results showed that more humid months have the largest variability. By contrast, the driest locations presented more variability on short timescales, probably due to the presence of a large number of clouds, even in very dry conditions. This characteristic can be of concern to Brazilian energy planning since the site is located in the most prominent region for solar energy generation. We also compared ground observations with satellite cloud variability, with 30-min resolution. For the same timescale, the results were promising, with a Pearson correlation of up to 0.93, depending on the site. However, when the frequency of the solar irradiance measurements increased, the correlation decreased. A solution may be to analyze a larger pixel area around the sites. Another option would be the use of downscaling methods. This topic, however, will be the subject of the future study. The most important result achieved in this study was the development of a simple methodology for evaluating the surface solar irradiance variability using cloud cover obtained from visible satellite imagery.