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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM43955
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
â The fast transformation of energy infrastructure has led to the adoption of clever grids, which leverage advanced technology for green energy management and cargo forecasting. synthetic Intelligence (AI)-driven optimization plays a important role in improving the performance of smart grids by means of permitting real-time energy distribution, demand forecasting, and fault detection. This examine explores the combination of AI strategies including gadget gaining knowledge of, deep mastering, and reinforcement studying in optimizing smart grid operations. The outcomes highlight how AI-powered forecasting models enhance strength performance, reduce operational fees, and decrease energy losses. moreover, this study discusses the demanding situations and boundaries of AI-driven optimization in smart grids, inclusive of information privateness concerns and computational complexities. The look at concludes by way of emphasizing the ability of AI in revolutionizing smart grid power management and presenting destiny guidelines for studies on this area.
KEYWORDS
Publication Date
4/6/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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