AI Innovation for Renewable Energy and Environmental Sustainability

The growing need for sustainable energy solutions has driven the integration of Artificial Intelligence (AI) into renewable energy systems, enabling the optimization of resource utilization, efficiency, and environmental impact. This study explores the transformative role of AI in addressing challenges such as intermittency, grid integration, and real-time decision-making in renewable energy sources, including solar, wind, and wave power. AI-driven innovations, such as predictive algorithms, reinforcement learning, and machine learning, have enhanced energy generation, storage, and distribution, significantly reducing carbon footprints and emissions. The research highlights real-world case studies where AI technologies have improved energy systems’ performance, stabilized grids, and supported demand-response strategies. Moreover, the paper examines future trends, including AI’s integration with blockchain, IoT, and big data analytics, alongside policy frameworks and international collaborations essential for fostering AI adoption. Recommendations emphasize investment in AI research, capacity building, affordable solutions, and public-private partnerships to maximize AI’s potential in advancing renewable energy sustainability. This paper underscores the critical role AI plays in achieving global climate goals and accelerating the transition to a low-carbon future.