Abstract
The traditional energy systems have changed their processes by using new artificial intelligence solutions for better energy management. These new technologies enhance the system performance and energy management across interconnected networks. This chapter explores how these new integrated systems and technologies are transformingthe energy generation, distribution, and storage for smart homes and industries. By leveraging technologies like machine learning, deep learning, edge computing, and federated learning, the traditional system is improved with more predictive, automated features. AI-enabled systems improve energy management, renewable energy forecasting, anomaly detection, and real-time decision-making. In the end, this chapter also discusses the future trends and emerging technologies, including blockchain and 5G/6G, for more advanced decentralized energy ecosystems.
| Original language | English |
|---|---|
| Title of host publication | Artificial Intelligence-Based Renewable Energy Systems |
| Subtitle of host publication | Standards, Communication Systems, and Data Networks |
| Publisher | Elsevier |
| Pages | 3-21 |
| Number of pages | 19 |
| ISBN (Electronic) | 9780443406188 |
| ISBN (Print) | 9780443406195 |
| DOIs | |
| Publication status | Published - 1 Jan 2026 |
Keywords
- Artificial intelligence
- Control engineering
- Deep learning
- Energy application
- Energy management
- Energy sustainability
- Energy systems
- Machine learning
- Supervisory control and data acquisition (SCADA)
- Sustainable development
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