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portada Physics-Aware Machine Learning for Integrated Energy Systems Management
Type
Physical Book
Collection
Advances in Intelligent Energy Systems
Year
2025
Pages
458
Format
Paperback
Dimensions
22.9x15.2 cm
ISBN13
9780443329845

Physics-Aware Machine Learning for Integrated Energy Systems Management

Behnam Mohammadi-Ivatloo;Mohammadreza Daneshvar;Kazem Zare;Jamshid Aghaei (Author) · Elsevier - Health Sciences Division · Paperback

Physics-Aware Machine Learning for Integrated Energy Systems Management - Behnam Mohammadi-Ivatloo;Mohammadreza Daneshvar;Kazem Zare;Jamshid Aghaei

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Synopsis "Physics-Aware Machine Learning for Integrated Energy Systems Management"

Physics-Aware Machine Learning for Integrated Energy Systems Management, a new release in the Advances in Intelligent Energy Systems series, guides the reader through this state-of-the-art approach to computational methods, from data input and training to application opportunities in integrated energy systems. The book begins by establishing the principles, design, and needs of integrated energy systems in the modern sustainable grid before moving into assessing aspects such as sustainability, energy storage, and physical-economic models. Detailed, step-by-step procedures for utilizing a variety of physics-aware machine learning models are provided, including reinforcement learning, feature learning, and neural networks. Supporting students, researchers, and industry engineers to make renewable-integrated grids a reality, this book is a holistic introduction to an exciting new approach in energy systems management.

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