An optimized approach for mapping solar irradiance in a mid-low latitude region based on a site-adaptation technique using Himawari-8 satellite imageries

Jen-Yu Han and Petr Vohnicky

Renewable Energy, 2022, vol. 187, issue C, 603-617

Abstract: Solar technologies play an important role in the renewable electric energy budget, so accurate solar maps are a crucial point for finding a suitable place for solar panel installation. This study proposes a method for solar irradiance mapping in mid-low latitude regions, and the method's site-adaptation process is performed by optimizing the Heliosat method through the REST2 clear-sky model, cloud albedo selection, new clear-sky index, and linear subtraction for bias removal. A local station with two pyranometers provided ground measurements. Site-adapted model results were used to create a calibrated solar map by linear regression adaptation. This study also provides the evaluation and site-adaption of another irradiance dataset in the Asian region from the Japan Aerospace Exploration Agency (JAXA). Heliosat model results with optimal cloud albedo showed high accuracy of 4.78 W/m2 MBE and 63.11 W/m2 RMSE, which can be improved using the site-adaptation process to 0.71 W/m2 MBE and 57.42 W/m2 RMSE. The selection of an optimal cloud albedo improved the model by approximately 20%. The JAXA dataset obtained a large overestimation of 56.72 W/m2 MBE, thereby highlighting the importance of site adaptation. This research's findings pave a new way for the creation of accurate site-adapted solar maps and databases.

Keywords: Solar irradiance; Solar energy mapping; Heliosat model; Rest2; Satellite images (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:187:y:2022:i:c:p:603-617

DOI: 10.1016/j.renene.2022.01.027

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