Leveraging artificial intelligence for optimizing renewable energy systems and enhancing climate sustainability

The transition toward sustainable energy systems has become an urgent global priority, particularly in developing economies facing persistent energy and climate challenges. This study explores how Artificial Intelligence (AI) can be leveraged to optimize renewable energy systems and promote climate sustainability in Nigeria. Using a mixed-methods approach that combined secondary data analysis with an extensive review of empirical literature, the research examined the extent to which AI enhances the efficiency, reliability, and environmental performance of renewable energy technologies. Findings reveal that AI applications such as machine learning, neural networks, and predictive analytics significantly improve energy demand forecasting, grid stability, and maintenance efficiency. These technologies contribute to reduced system losses and lower carbon emissions, aligning with Nigeria’s commitment to the Sustainable Development Goals (SDGs) and the Paris Climate Agreement. However, the study also identifies critical challenges, including limited data infrastructure, inadequate technical capacity, and weak policy frameworks that hinder large-scale AI deployment in Nigeria’s energy sector. The study concludes that AI represents a transformative pathway for enhancing renewable energy performance and achieving climate resilience. To maximize its potential, Nigeria must strengthen institutional support, invest in digital infrastructure, and promote collaborative research between academia, industry, and government. By integrating AI into energy governance, Nigeria can accelerate its transition toward a low-carbon, efficient, and sustainable energy future.