Structured into four cohesive parts—Preliminaries, Architecture, Control, and Applications—the book integrates foundational theory with engineering practice. It elaborates on hierarchical and distributed control structures, introduces adaptive dynamic programming (ADP) and learning-based optimization frameworks, and elucidates the role of digital intelligence in enhancing real-time decision-making and operational robustness. Comprehensive case studies drawn from industrial parks, islanded systems, and transportation energy networks demonstrate practical approaches toward achieving low-carbon, efficient, and resilient energy integration.
This book serves as both a scholarly reference and a methodological guide for advancing intelligent control, coordination, and optimization in next-generation sustainable energy infrastructures.