Digital Twins for Building Optimization: Enhancing Energy and Comfort
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Beschreibung
This book bridges the gap between theoretical research and practical applications in the field of smart building energy management. With a structure that offers a blend of theoretical concepts, practical implementations, and case studies, the book is designed to serve as a comprehensive resource for researchers, practitioners, and students. It navigates through control strategies, meta-heuristic approaches, intelligent controller designs, and the balancing of energy efficiency with occupant comfort, all underpinned by both academic research and industry practices. Specific pedagogical examples involving Python™ have been used within the book to aid the understanding of certain concepts, in addition to a chapter dedicated to EnergyPlus™.
This book bridges the gap between theoretical research and practical applications in the field of smart building energy management. With a structure that offers a blend of theoretical concepts, practical implementations, and case studies, the book is designed to serve as a comprehensive resource for researchers, practitioners, and students. It navigates through control strategies, meta-heuristic approaches, intelligent controller designs, and the balancing of energy efficiency with occupant comfort, all underpinned by both academic research and industry practices. Specific pedagogical examples involving Python™ have been used within the book to aid the understanding of certain concepts, in addition to a chapter dedicated to EnergyPlus™.
Bridges the gap between theoretical research and practical applications in the field of smart building energy management Combines EnergyPlus simulation with Python-based control and AI algorithms Serves as a comprehensive resource for researchers, practitioners, and student
Autor*in
Mubashir Hussain Wani
Themen in »Digital Twins for Building Optimization: Enhancing Energy and Comfort«
Building Energy Management Systems (BEMS) Building Digital Twins Cognitive Cities Energy Optimization Evolutionary Algorithms (EAs) Machine Learning (ML) Multi-Criteria Decision Making (MCDM)