Editors: Sugandha Singh, Inam Ul Haq, Sachin Ahuja, Akib Mohi Ud Din Khanday, Neha Sharma

Series Title: Algorithm Management Optimization

Artificial Intelligence in Wind Energy: Transforming Green Energy Generation

Volume 1

eBook: US $79 Special Offer (PDF + Printed Copy): US $135
Printed Copy: US $95
Library License: US $316
ISBN: 979-8-89881-505-9 (Print)
ISBN: 979-8-89881-504-2 (Online)
Year of Publication: 2026
DOI: 10.2174/97988988150421260101

Introduction

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.

Target Readership :

Researchers, academics, and industry professionals in renewable energy, electrical engineering, and artificial intelligence.

Foreword

- Pp. i
Pramod Singh Rathore
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Preface

- Pp. ii
Sugandha Singh, Inam Ul Haq, Sachin Ahuja, Akib Mohi Ud Din Khanday, Neha Sharma
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List of Contributors

- Pp. iii-iv (2)

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Introduction to AI in Wind Energy

- Pp. 1-26 (26)
Mamta*

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AI-Driven Decision-Making Tools in Wind Energy

- Pp. 27-50 (24)
Vandita Nandal, Himani Uppal, Inam Ul Haq*, Anand Kumar Gupta

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Machine Learning Models for Resource Optimization in AI-Driven Wind Energy Systems

- Pp. 51-76 (26)
Inderdeep Kaur*, Inzimam Ul Hassan

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The Integration of AI and Green Energy: Innovations and Operational Improvements

- Pp. 77-97 (21)
Shivani, Satinder Bal Gupta*

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Wind Energy Prediction Utilizing Artificial Intelligence on Green Energy Transformation

- Pp. 98-115 (18)
Vikas Verma, Tiyas Sarkar*, Manik Rakhra

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Intelligent Winds: Transforming Wind Energy through Machine Learning

- Pp. 116-131 (16)
Sakshi, Arushi Aggarwal, Inam Ul Haq*

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AI for Wind Turbine Performance and Maintenance

- Pp. 132-165 (34)
Harsh Kumar, Malik Muzamil Ishaq*

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Hybrid Wind-Solar Systems Powered by AI

- Pp. 166-204 (39)
Himani Uppal, Vandita Nandal, Sheetal*, Inam UI Haq

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Forecasting the Power Generation of Wind Turbines through Advanced Artificial Intelligence Techniques

- Pp. 205-220 (16)
Manik Rakhra, Tiyas Sarkar*, Vikas Verma

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The Future of Resource Optimization with AI and Machine Learning

- Pp. 221-231 (11)
Khalid Hafiz Mir*, Anzah Bashir, Hashim Mohi u din Dar

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Optimizing Wind Farm Site Selection with AI

- Pp. 232-263 (32)
Vandita Nandal, Himani Uppal, Syed Zoofa Rufai*, Inam Ul Haq

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Subject Index

- Pp. 264-269 (6)
Sugandha Singh, Inam Ul Haq, Sachin Ahuja, Akib Mohi Ud Din Khanday, Neha Sharma
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