Artificial Intelligence in Renewable Energy Systems: Applications, Optimization, and Future Prospects
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Abstract
The intermittent nature of renewable energy sources (RES) like solar and wind poses significant challenges for grid stability, asset optimization, and energy distribution. This paper reviews the state-of-the-art Artificial Intelligence (AI) tools and machine learning algorithms utilized to solve these bottlenecks. We explore applications across predictive forecasting, smart grid management, and asset maintenance, demonstrating how AI transitions the energy sector from reactive management to proactive optimization.
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This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.