aceArtificial Intelligence for Smart Grid and Renewable Energy Management: A Review of Techniques, Applications, and Future Directions
Intermittent renewable generation, volatile loads, and concerns over grid stability have become defining features of modern power systems. Addressing these challenges with Artificial Intelligence (AI) and Machine Learning (ML) is attracting growing attention, including through better forecasting, automated demand response, optimized energy storage, and smart grid fault detection. This paper highlights the various AI-based techniques developed across the smart grid landscape, ranging from solar and wind forecasti…
Variable renewable output and volatile demand strain power systems, and AI grid tools face unresolved privacy, interpretability, scalability and cybersecurity challenges.
The proposed three-layer framework is conceptual and has not been validated empirically, so its real-world performance is unknown.
Evidence
- Peer-reviewedInternational Journal of Advanced Research in Science Communication and Technology2026-10-16
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Truvace Impact Record TRV-2026-1747, v1: “Artificial Intelligence for Smart Grid and Renewable Energy Management: A Review of Techniques, Applications, and Future Directions.” Truvace, 2026-10-17. /record/TRV-2026-1747 (accessed at citation time). sha256 77f0cc69a9a86bf9…
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