September 18, 2025Global Journal of Engineering and Technology Advances

Artificial Intelligence-enabled smart grid systems for real-time load forecasting, fault detection, renewable energy integration and optimization

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AI-enabled smart grids improve load forecasting, enhancing efficiency and stability in energy systems.
Fault detection technologies driven by AI swiftly identify anomalies, preventing potential failures and enhancing grid resilience.
The integration of renewable energy sources is optimized through AI, addressing challenges associated with energy intermittency.
Challenges include data privacy and cybersecurity risks, pointing to the need for robust solutions in AI implementations.

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Implication

Observational analysis highlights enhanced load forecasting and fault detection in smart grids, suggesting AI's critical role in renewable energy integration.

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Iyaniwura et al. (2025) studied this question.

synapsesocial.com/papers/68d433b8713b0b5dfea7383a https://doi.org/10.30574/gjeta.2025.24.3.0272

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Implication

Observational analysis highlights enhanced load forecasting and fault detection in smart grids, suggesting AI's critical role in renewable energy integration.

Artificial Intelligence-enabled smart grid systems for real-time load forecasting, fault detection, renewable energy integration and optimization

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Discussion

Implication

Cite This Study

Artificial Intelligence-enabled smart grid systems for real-time load forecasting, fault detection, renewable energy integration and optimization

Key Points

Discussion

Implication

Cite This Study

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