Evaluation of Irradiance Decomposition Models and Their Predictor

This study presents a comprehensive approach to developing models for decomposing global solar radiation in to its diffuse and direct components, a critical step in solar energy applications. Utilizing data from multiple geographical regions and Köppen-Geiger climate zones, the research ensures a broad understanding of the environmental factors affecting solar radiation. The study meticulously selects predictors through multiple feature selection techniques, focusing on capturing essential information while minimizing redundancy. Single-predictor models are developed to provide insights into the relationships between selected predictors and the diffuse fraction, while two multi-predictor models demonstrates the potential for more accurate estimations by leveraging the collective predictive power of multiple variables. One of the developed models, called Nested, performs better than other state-of-the-art universal models, while performing slightly worse than the best climate-specific model in terms of three performance metrics. The research lays a solid foundation for future studies and practical applications in the solar energy sector, emphasizing the need for further testing of techniques and procedures for decomposition model development.