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.

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