Harnessing Machine Learning to Analyze Renewable Energy Research in Latin America and the Caribbean

The transition to renewable energy is essential for mitigating climate change and promoting sustainable development, particularly in Latin America and the Caribbean (LAC). Despite its vast potential, the region faces structural and economic challenges that hinder a sustainable energy transition. Understanding scientific production in this field is key to shaping policy, investment, and technological progress. The primary objective of this study is to conduct a large-scale, data-driven analysis of renewable energy research in LAC, mapping its thematic evolution, collaboration networks, and key research trends over the past three decades. To achieve this, machine learning-based topic modeling and network analysis were applied to examine research trends in renewable energy in LAC. A dataset of 18,780 publications (1994–2024) from Scopus and Web of Science was analyzed using Latent Dirichlet Allocation (LDA) to uncover thematic structures. Network analysis assessed collaboration patterns and regional integration in research. Findings indicate a growing focus on solar, wind, and bioenergy advancements, alongside increasing attention to climate change policies, energy storage, and microgrid optimization. Artificial intelligence (AI) applications in energy management are emerging, mirroring global trends. However, research disparities persist, with Brazil, Mexico, and Chile leading output while smaller nations remain underrepresented. International collaborations, especially with North America and Europe, play a crucial role in research development. Renewable energy research supports Sustainable Development Goals (SDGs) 7 (Affordable and Clean Energy) and 13 (Climate Action). Despite progress, challenges remain in translating research into policy and addressing governance, financing, and socio-environmental factors. AI-driven analytics offer opportunities for improved energy planning. Strengthening regional collaboration, increasing research investment, and integrating AI into policy frameworks will be crucial for advancing the energy transition in LAC. This study provides evidence-based insights for policymakers, researchers, and industry leaders.