Optimizing Hybrid Renewable Energy Systems for Sustainable Power Generation: A Machine Learning Approach

The increasing need for sustainable energy solutions has driven research into hybrid energy systems, particularly those leveraging solar and wind energy. This study proposes an optimized hybrid energy system employing machine learning to enhance efficiency and predictability in renewable energy production and distribution. The integration of advanced algorithms and real-time data analytics ensures improved performance and reduces dependence on fossil fuels, addressing pressing climate change concerns. Machine learning models not only optimize energy allocation but also predict system behaviour under varying conditions, ensuring robustness and adaptability in dynamic environments.