A Hybrid Fuzzy Logic Neural Network System for Solar Radiation Forecasting: A Theoretical Framework and Case Study of Kuwait

Solar radiation forecasting is critical for optimizing renewable energy systems, particularly in regions with high solar potential like Kuwait. This paper presents a theoretical framework for a hybrid forecasting system that combines fuzzy logic and neural networks to predict solar radiation with high accuracy. The proposed system leverages the Adaptive Neuro-Fuzzy Inference System (ANFIS) to handle the inherent uncertainty and variability in meteorological data. While the study is primarily theoretical due to limitations in data and resources, it provides a comprehensive review of existing methods and highlights the potential of hybrid systems for improving solar radiation forecasting. The paper concludes with a discussion of the limitations and suggests future work involving experiments to validate the proposed framework.