REVIEW ON THE RECENT ADVANCEMENT IN ARTIFICIAL INTELLIGENCE (AI) GENERATIVE DESIGN AND MACHINE LANGUAGE APPLICATION IN SOLAR AND WIND ENERGY

Abstract

This review examines recent advancements in the integration of AI generative design and machine learning techniques within the scope of renewable energy, with a focus on solar and wind energy systems. By utilizing current literature and cutting-edge research, this study elucidates the multifaceted applications of AI in optimizing the design, operation, and management of renewable energy infrastructures. Specifically, AI generative design methodologies are explored for their ability to enhance the efficiency and performance of solar panel layouts and wind turbine configurations. Moreover, machine learning algorithms are investigated for their capacity to predict energy generation patterns, optimize resource allocation, and enable autonomous decision-making in renewable energy systems. Future research directions and challenges, including data availability, model interpretability, and scalability, are also discussed, providing insights for further advancements in the field.