Mohammadreza aghaei (6 Ergebnisse)

Zustand: New. In English.

Zustand: New. In English.

Zustand: New. Provides a clear grounding in the fundamentals of DTT and opportunities for this innovative method in the energy industry Guides students and industry practitioners step-by-step from the discovery of techniques to practical model building.

Zustand: New. Outlines the challenges, opportunities, and applications for utilizing physics-aware machine learning to support renewable energy integration to the modern gridCovers a wide variety of techniques, from fundamental principles to security con.

Taschenbuch. Zustand: Neu. Neuware - Digital Twin Technology for the Energy Sector: Fundamental, Advances, Challenges, and Applications introduces the energy sector to this innovative technology and its potential for supporting energy transition. The book outlines the fundamentals of digital twin technology (DTT), giving readers a thorough grounding in its theory and use. Additional chapters provide practical, real-world options for applying the technology in a variety of energy sectors, from wind, solar, and hydropower, to the electrical industry and mobility. Its potential uses for energy flexibility, managing supply and demand in electric grids, and energy modeling in real time are also given significant attention.Including insights from a wide range of expert researchers and industry professionals, this book will guide readers from their first steps in DTT to developing innovative applications for the energy sector of the future.…

Taschenbuch. Zustand: Neu. Neuware - 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.…