AI Technologies for Renewable Energy Systems and Intelligent Grid Optimization (Paperback)

Paperback. The transition to renewable energy is fundamentally reshaping modern energy systems. As solar, wind, geothermal, and other renewable resources play an increasingly prominent role in global energy strategies, their variable generation patterns and distributed deployment create new challenges for forecasting, system control, energy storage, and grid management. Meeting these challenges requires more advanced approaches to balancing supply and demand, improving operational efficiency, and maintaining system reliability. Artificial intelligence (AI) offers powerful capabilities for addressing these needs through data-driven forecasting, predictive analytics, optimization, automation, and intelligent decision-making. By enabling more responsive and adaptive energy systems, AI is becoming a critical tool in supporting the large-scale integration of renewable energy technologies. AI Technologies for Renewable Energy Systems and Intelligent Grid Optimization presents interdisciplinary perspectives on the role of AI in advancing renewable energy systems and developing more efficient, resilient, and intelligent electricity networks. This book explores AI applications across renewable energy generation, energy storage systems, smart grids, electric vehicle charging infrastructure, and building-scale energy management. Beyond individual technologies, it addresses the growing interconnectedness of renewable generation assets, storage infrastructure, buildings, transportation systems, and electric grids, highlighting the opportunities and challenges associated with increasingly integrated energy ecosystems. Covering topics such as capacity improvement, grid resilience, and machine learning, this book serves as an essential resource for academics, graduate and postgraduate students, engineers, energy professionals, policymakers, and researchers seeking to understand the future of AI-enabled sustainable energy systems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…