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The Journal of Advanced Multidisciplinary Research (JAMR) is a peer-reviewed, international hybrid journal dedicated to advancing high-quality research across emerging technological, scientific, and societal disciplines. By bridging theory and practice, the journal offers a platform for global researchers, academics, and industry professionals to publish high-impact contributions.
Volume 1, Issue 1, Pages 116-130
As power grids transition toward sustainable sources, integrating intermittent renewable energy systems poses significant stability and efficiency challenges. This paper presents an AI-driven framework designed to optimize energy distribution across hybrid renewable microgrids. Utilizing a combination of deep reinforcement learning and predictive forecasting models, our approach anticipates dynamic demand fluctuations while maintaining grid balance. Experimental results demonstrate a 14.2% reduction in overall transmission losses and a 22% improvement in peak-load response efficiency compared to traditional management strategies. These findings underscore the potential of scalable machine learning algorithms in modernizing clean energy infrastructure.
Artificial Intelligence, Renewable Energy, Smart Grids, Machine Learning, Energy Efficiency.
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