Applications of deep machine learning in future energy systems /
This book explores the applications of deep machine learning in the realm of future energy systems, providing insights into the integration of artificial intelligence in energy management and control systems. The book is edited by Khooban and features contributions from experts in the field. It delv...
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| Format: | eBook |
| Language: | English |
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Amsterdam :
Elsevier,
2024.
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| Online Access: | Connect to the full text of this electronic book |
| Summary: | This book explores the applications of deep machine learning in the realm of future energy systems, providing insights into the integration of artificial intelligence in energy management and control systems. The book is edited by Khooban and features contributions from experts in the field. It delves into various topics including machine learning techniques for forecasting, fault detection, and control operations in energy systems, digital twin-assisted design, intelligent charging stations for electric vehicles, and frequency control of power grids under cyber attacks. The book aims to equip researchers and practitioners with the latest methodologies and case studies for implementing machine learning in energy systems, targeting an audience of professionals and academics in electrical and computer engineering. The content is grounded in current research and includes practical insights on the use of technologies like MATLAB in energy system design. |
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| Physical Description: | 1 online resource |
| ISBN: | 9780443214318 044321431X |