1. Introduction
Renewable energy integration is crucial for sustainable development...
2. Challenges
Intermittency and grid stability issues...
3. AI-Based Solution
Machine learning for energy prediction...
4. Case Studies
Real-world implementation results...
5. Conclusion
AI significantly improves renewable integration...
References
[1] IEA (2024). Renewable Energy Report.
[2] Anderson, L. (2024). Energy Systems Journal.
Renewable Energy Integration in Smart Grids: Challenges and Solutions
Michael Davis
University of Tokyo
DOI: 10.1234/journal.v2.1.009
Published: July 15, 2024
Research Articles
Abstract
This research addresses the challenges of integrating renewable energy sources into smart grid systems. We analyze the intermittency problem of solar and wind power and propose AI-based prediction models for better grid management. The solution was tested using data from three major power grids, showing 30% improvement in renewable energy utilization.
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Article Info
-
Issue:
Vol. 1 No. 2 (2024): Spring Edition -
Section:
Research Articles -
Submitted:
June 20, 2024 -
Published:
July 15, 2024 -
DOI:
10.1234/journal.v2.1.009
How to Cite
Michael Davis (2024). "Renewable Energy Integration in Smart Grids: Challenges and Solutions." Abhidakara Jurnal, 1(2). doi:10.1234/journal.v2.1.009