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 (Print)
ISBN: 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.