This book offers a practical, implementation-ready guide to operating and controlling contemporary power systems with high renewable energy penetration. It addresses real-world challenges such as frequency regulation, dynamic economic emission dispatch, demand side management, PHEV integration, and virtual power plant optimization.

This book:

• Highlights the operational and regulatory challenges associated with the increasing integration of renewable energy sources.
• Presents advanced mathematical models and cutting-edge machine learning methodologies to tackle intricate issues in control, forecasting, and optimization within modern power systems.
• Provides an excellent foundation for the core concepts and applications of artificial intelligence and machine learning solutions in the operation and control of contemporary power systems.
• Discusses strategies to address the challenges of variability, intermittency, and integration encountered with renewable energy sources.
• Showcases a detailed overview of advanced control strategies, self-healing methodologies, hybrid demand-side management techniques, and sophisticated scheduling algorithms.

It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communication engineering, computer engineering, renewable energy, clean technologies, and environmental engineering.