Intelligent Learning Approaches for Renewable and Sustainable Energy

著者名：Guerrero, Josep M. (EDT)/Gupta, Pankaj (EDT)/Kandari, Ritu (EDT)/Micallef, Alexander (EDT)

Elsevier（2024/02/21発売）

• 言語：ENG
• ISBN：9780443158063
• eISBN：9780443158070

Description

Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy.The book begins by introducing the intelligent learning approaches, and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. The second section of the book provides detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, and optimization, supported by case studies, figures, schematics, and references.This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence.- Explores cutting-edge intelligent techniques and their implications for future energy systems development- Opens the door to a range of applications across forecasting, supply and demand, energy management, optimization, and more- Includes a range of case studies that provide insights into the challenges and solutions in real-world applications

Table of Contents

Section I: Introduction to intelligent learning approaches for renewable and sustainable energy 1. Artificial Intelligence-based sustainability in energy 2. Machine-learning-based sustainability in energy 3. Transforming the grid: AI, ML, Renewable, Storage, EVs, and Prosumers 4. Role of intelligent techniques in large-scale integration of renewable energy 5. Variability of renewable energy generation and flexibility initiatives Section II: Applications of intelligence learning approaches for renewable and sustainable energy 6. Intelligent learning models for renewable energy forecasting 7. Intelligent learning models for balancing supply and demand 8. Intelligent learning analysis for a flexibility energy approach towards renewable energy integration 9. Intelligent learning analysis for energy management 10. Intelligent learning approaches for demand-side controller for BIPVs integrated buildings 11. Intelligent learning approaches for single and multi-objective optimization methodology 12. Intelligent learning approaches for optimization of integrated energy systems