Optimizing solar energy planning: A spatial zoning method based on characterized dimensionless radiation profiles

Spatiotemporal distribution of solar energy resources is crucial for overall energy development; however, most studies face challenges in achieving reliability and high accuracy when completing solar radiation datasets across regions and also assume fixed climate zones, overlooking randomness from regional climatic inconsistencies. This study proposed a method for identifying dimensionless characterized solar radiation profiles to fill in missing solar radiation values. Benefiting from the characteristic attributes contained in the dimensionless profiles, prejudgment based on multiple sets of profiles can provide a visual window for validating climatic consistency. A case study on Kyushu shows that the proposed method achieves high accuracy on untrained data, with R² values of 0.92-0.93 daily and 0.89-0.90 hourly. A spatiotemporal solar radiation map of Kyushu was developed, showing average annual radiation of 4616-5320 MJ m^-2 yr^-1, and a weather-stochasticity-driven zoning approach that divides the region into four zones.