Comprehensive review of artificial intelligence applications in renewable energy systems: current implementations and emerging trends
Abstract As the world faces pressing climate and energy challenges, Artificial Intelligence is proven as a transformative force in advancing renewable energy systems. This study reviews the current and future applications of Artificial Intelligence in renewable energy, highlighting its transformativ...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-07-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-025-01178-7 |
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| Summary: | Abstract As the world faces pressing climate and energy challenges, Artificial Intelligence is proven as a transformative force in advancing renewable energy systems. This study reviews the current and future applications of Artificial Intelligence in renewable energy, highlighting its transformative role in enhancing the efficiency, reliability, and scalability of renewable energy systems. The study draws from over 400 recent publications, selected based on their relevance to Artificial Intelligence and renewable energy systems. We discuss the use of Artificial Intelligence techniques including machine learning, deep learning, and reinforcement learning models for optimizing energy production, forecasting demand, predictive maintenance, and managing decentralized energy systems. Emerging fields such as quantum machine learning and Artificial Intelligence-augmented reality are also considered because of their potential to transform energy infrastructures. The survey reviews significant innovations in wind and solar energy, energy storage, and smart grid technologies, focusing on how Artificial Intelligence addresses challenges like intermittency and variability. Furthermore, we discuss the importance of big data, the Internet of Things, and real-time analytics in advancing Artificial Intelligence models, along with the evolving landscape of Artificial Intelligence-driven policy and market modeling for renewable energy adoption. Real-world case studies, like Google’s collaboration with DeepMind for optimizing wind energy output and Australia’s National Electricity Market integrating Artificial Intelligence for grid stability, underscore the practical impact of Artificial Intelligence in renewable energy. This paper highlights challenges that are hindering Artificial Intelligence adoption in renewable energy systems and offers recommendations for improving the available technology to maximize Artificial Intelligence’s potential in promoting sustainable energy and addressing climate change. |
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| ISSN: | 2196-1115 |