Artificial Intelligence in Wind Energy: Transforming Green Energy Generation
Language: English
Published by Bentham Science Publishers, 2026
- Softcover
- New

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- Title
- Artificial Intelligence in Wind Energy: Transforming Green Energy Generation
- Author
- Singh, Sugandha
- Publisher
- Bentham Science Publishers
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798898815066
Algorithm Management Optimisation (Vol. 1) Artificial Intelligence in Wind Energy: Transforming Green Energy Generation explores the integration of Artificial Intelligence (AI) with wind energy systems to address key challenges in renewable energy. It highlights how machine learning and data-driven techniques improve efficiency, reliability, and sustainability in wind power generation through better forecasting, optimisation, and decision-making.
The book begins with the fundamentals of renewable energy and wind systems, followed by AI and machine learning concepts relevant to energy applications. It covers wind resource assessment, forecasting models, turbine performance optimisation, predictive maintenance, and wind farm site selection. Advanced topics include smart grid integration, hybrid renewable systems, explainable AI, and real-time analytics, supported by practical case studies.
Key Features:
-Detailed discussions on the integration of AI and machine learning in wind energy systems.
-Coverage of forecasting, optimisation, and predictive maintenance.
-Focuses on smart grids and hybrid renewable energy systems with discussion on their optimisation, forecasting and predictive maintenance.
-Real-world case studies and practical applications with discussions on ethical and responsible AI use in energy.
The book begins with the fundamentals of renewable energy and wind systems, followed by AI and machine learning concepts relevant to energy applications. It covers wind resource assessment, forecasting models, turbine performance optimisation, predictive maintenance, and wind farm site selection. Advanced topics include smart grid integration, hybrid renewable systems, explainable AI, and real-time analytics, supported by practical case studies.
Key Features:
-Detailed discussions on the integration of AI and machine learning in wind energy systems.
-Coverage of forecasting, optimisation, and predictive maintenance.
-Focuses on smart grids and hybrid renewable energy systems with discussion on their optimisation, forecasting and predictive maintenance.
-Real-world case studies and practical applications with discussions on ethical and responsible AI use in energy.
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