Intelligent Urban Systems: IoT-Driven Energy Management and Smart City Optimization : Renewable Energy Systems and Technologies, Volume 2
Language: English
Published by Springer, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 204.25
Quantity: 1 available
Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - This comprehensive volume delivers cutting-edge solutions for integrating artificial intelligence into renewable energy systems, addressing critical challenges in sustainable energy transition. Readers will discover innovative approaches to optimizing photovoltaic systems, wind energy conversion, smart grids, and hybrid energy storage through advanced machine learning algorithms and intelligent control strategies.The book presents practical applications spanning MPPT optimization techniques, predictive maintenance using SCADA data, IoT-based monitoring systems, and AI-driven fault detection in power electronics. Contributors explore emerging topics including green hydrogen production, electric vehicle control systems, energy forecasting with deep learning, and autonomous microgrid management. Special emphasis is placed on real-world implementations tested in diverse environmental conditions.Featuring contributions from leading international researchers and practitioners, this work bridges the gap between academic research and industrial application. Engineers, researchers, and graduate students working in renewable energy, power systems, and artificial intelligence will find invaluable insights for developing efficient, resilient, and sustainable energy solutions that meet urgent climate and energy security challenges.…
Seller Inventory # 9783032338501
- Title
- Intelligent Urban Systems: IoT-Driven Energy Management and Smart City Optimization : Renewable Energy Systems and Technologies, Volume 2
- Author
- Mustapha Hatti
- Publisher
- Springer
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3032338506
- ISBN 13
- 9783032338501
- Item weight
- 920 grams
- Dimensions
- 235x155x33 mm
This comprehensive volume delivers cutting-edge solutions for integrating artificial intelligence into renewable energy systems, addressing critical challenges in sustainable energy transition. Readers will discover innovative approaches to optimizing photovoltaic systems, wind energy conversion, smart grids, and hybrid energy storage through advanced machine learning algorithms and intelligent control strategies.
The book presents practical applications spanning MPPT optimization techniques, predictive maintenance using SCADA data, IoT-based monitoring systems, and AI-driven fault detection in power electronics. Contributors explore emerging topics including green hydrogen production, electric vehicle control systems, energy forecasting with deep learning, and autonomous microgrid management. Special emphasis is placed on real-world implementations tested in diverse environmental conditions.
Featuring contributions from leading international researchers and practitioners, this work bridges the gap between academic research and industrial application. Engineers, researchers, and graduate students working in renewable energy, power systems, and artificial intelligence will find invaluable insights for developing efficient, resilient, and sustainable energy solutions that meet urgent climate and energy security challenges.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This comprehensive volume delivers cutting-edge solutions for integrating artificial intelligence into renewable energy systems, addressing critical challenges in sustainable energy transition. Readers will discover innovative approaches to optimizing photovoltaic systems, wind energy conversion, smart grids, and hybrid energy storage through advanced machine learning algorithms and intelligent control strategies.
The book presents practical applications spanning MPPT optimization techniques, predictive maintenance using SCADA data, IoT-based monitoring systems, and AI-driven fault detection in power electronics. Contributors explore emerging topics including green hydrogen production, electric vehicle control systems, energy forecasting with deep learning, and autonomous microgrid management. Special emphasis is placed on real-world implementations tested in diverse environmental conditions.
Featuring contributions from leading international researchers and practitioners, this work bridges the gap between academic research and industrial application. Engineers, researchers, and graduate students working in renewable energy, power systems, and artificial intelligence will find invaluable insights for developing efficient, resilient, and sustainable energy solutions that meet urgent climate and energy security challenges.
"About the title" may belong to another edition of this title.
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