Algorithm Management Optimization (Vol. 1)  Artificial Intelligence in Wind Energy: Transforming Green Energy Generation

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

Series Title: Algorithm Management Optimization

Algorithm Management Optimization (Vol. 1) Artificial Intelligence in Wind Energy: Transforming Green Energy Generation

Volume 1

ISBN: 979-8-89881-505-9
eISBN: 979-8-89881-504-2 (Online)

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.

Preface

In the era of renewable energy, wind power stands as a key player in the global push for sustainable energy solutions. "Artificial Intelligence in Wind Energy: Transforming Green Energy Generation" explores how Artificial Intelligence (AI) is revolutionizing wind energy systems, improving efficiency, and driving the transition to cleaner energy sources. This book delves into the powerful synergy between AI and wind energy, offering practical insights and real-world examples of AI’s impact on the wind energy sector. From resource assessment to performance optimization and grid integration, this book covers how AI-driven decision-making tools and machine learning models for resource optimization enhance every aspect of wind energy generation. Readers will discover how predictive analytics in operations management enables real-time monitoring, efficiency improvements, and cost reduction. The book also discusses ethical considerations in algorithmic management, ensuring that AI is implemented responsibly in renewable energy applications. Practical examples, case studies, and applications in real-world scenarios illustrate AI's transformative potential in areas such as wind prediction, site selection, turbine maintenance, and hybrid energy systems. Additionally, the chapters explore the economic and environmental benefits of AI, alongside emerging trends and challenges in the field.

Sugandha Singh
School of Engineering and Technology
Noida International University
Greater Noida, Uttar Pradesh
India

Inam Ul Haq
School of Engineering and Technology (SET)
CGC University, Mohali, Punjab
India

Sachin Ahuja
Department of Engineering
Chandigarh University, Mohali, Punjab
India

Akib Mohi Ud Din Khanday
Department of Information Technology
Cluster University of Srinagar
Jammu and Kashmir
India

&

Neha Sharma
Department of Computer Science and Engineering
School of Engineering and Technology
Shree Guru Gobind Singh Tricentenary University
Gurugram, India