Solar Radiation

Solar radiation research focuses on accurately predicting and modeling sunlight's intensity and distribution for various applications. Current efforts utilize machine learning, particularly deep learning architectures like Bayesian Neural Networks, Conditional Generative Adversarial Networks, and Gradient Boosting Regressors, to improve prediction accuracy and efficiency across diverse contexts, from optimizing solar energy harvesting in Concentrating Solar Power plants and domestic heating systems to simulating sunlight access in urban planning and greenhouse lighting control. These advancements offer significant potential for improving the efficiency and sustainability of energy systems, optimizing urban design for human comfort, and enhancing precision agriculture.