The survey by Rachmad Andri Atmoko offers a comprehensive overview of how artificial intelligence is reshaping modern electricity networks. By integrating AI into smart grids, utilities can automate fault detection, optimize demand response, and accelerate renewable energy integration. Predictive maintenance powered by deep learning and deep reinforcement learning identifies subtle anomalies before they trigger outages, outperforming legacy threshold‑based systems and reducing maintenance costs.

Demand‑side management models such as CNN‑LSTM and heuristic optimizers align consumption with grid constraints, lowering peak loads and operational expenses. Hybrid neural networks and physics‑informed models enhance forecasting accuracy for wind and solar generation, mitigating curtailment and improving grid stability. Real‑time data processing through federated learning preserves consumer privacy while enabling rapid decision‑making across distributed sensors.

Despite these advances, challenges remain: data interoperability, scalability, regulatory alignment, and cybersecurity. Addressing these barriers will be essential for utilities to deploy AI at scale and realize the full economic and environmental benefits of smarter, more resilient power systems.