Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing.
Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector.
1. Chapter 2 Smart energy and electric power system: current trends and new intelligent perspectives and introduction to AI and power system - p. 19 2. Chapter 3 Recent developments of smart energy networks and challenges - p. 37 3. Chapter 4 A smart and efficient IoT-AI and ML-based multifunctional system for multilevel power distribution management - p. 49 4. Chapter 5 A survey on AI- and ML-based demand forecast analysis of power using IoT-based SCADA - p. 65 5. Chapter 6 Impact of artificial intelligence techniques in distributed smart grid monitoring system - p. 79 6. Chapter 7 Smart power quality control measures - p. 105 7. Chapter 8 Directional overcurrent relay coordination optimization - p. 121 8. Chapter 9 Monitoring of wind power control in microgrid - p. 147 9. Chapter 10 Cyber attacks, security data detection, and critical loads in the power systems - p. 169 10. Chapter 11 Blockchain-based secured payment in IoE - p. 185 11. Index - p. 201
Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing.
Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector.
1. Chapter 2 Smart energy and electric power system: current trends and new intelligent perspectives and introduction to AI and power system - p. 19 2. Chapter 3 Recent developments of smart energy networks and challenges - p. 37 3. Chapter 4 A smart and efficient IoT-AI and ML-based multifunctional system for multilevel power distribution management - p. 49 4. Chapter 5 A survey on AI- and ML-based demand forecast analysis of power using IoT-based SCADA - p. 65 5. Chapter 6 Impact of artificial intelligence techniques in distributed smart grid monitoring system - p. 79 6. Chapter 7 Smart power quality control measures - p. 105 7. Chapter 8 Directional overcurrent relay coordination optimization - p. 121 8. Chapter 9 Monitoring of wind power control in microgrid - p. 147 9. Chapter 10 Cyber attacks, security data detection, and critical loads in the power systems - p. 169 10. Chapter 11 Blockchain-based secured payment in IoE - p. 185 11. Index - p. 201
