Advances of Artificial Intelligence in a Green Energy Environment

Pandian Vasant, Joshua Thomas, Elias Munapo, Gerhard-Wilhelm Weber

• Publisher: Academic Press
• Year: 2022
• Print ISBN:
  9780323897853
• eBook ISBN:
  9780323885744
• Topic: Physical Sciences
• Subtopic: Energy

Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern. Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy. Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry. - Looks at new techniques in artificial intelligence (AI) reducing the dimension of data coverage worldwide - Chapters include AI methodologies using enhanced hybrid swarm-based optimization algorithms - Includes flowchart diagrams for exampling optimizing techniques

Table of contents

• Cover
• Front Matter
• Table of Contents
• Copyright
• Contributors
• About the editors
• Preface
• Acknowledgments
• List of Illustrations
• List of Tables
• Chapter 1 : Application of some ways to intensify the process of anaerobic bioconversion of organic matter
• Chapter 2 : Disasters impact assessment based on socioeconomic approach
• Chapter 3 : Uninterruptible power supply system of the consumer, reducing peak network loads
• Chapter 4 : Optimization of the anaerobic conversion of green biomass into volatile fatty acids for further production of high-calorie liquid fuel
• Chapter 5 : Life cycle cost and life cycle assessment: an approximation to understand the real impacts of the Electricity Supply Industry
• Chapter 6 : Comparison of open access multi-objective optimization software tools for standalone hybrid renewable energy systems
• Chapter 7 : Optimization of the organic waste anaerobic digestion in biogas plants through the use of a vortex layer apparatus
• Chapter 8 : Search of regularities in data: optimality, validity, and interpretability
• Chapter 9 : Artificial intelligence techniques for modeling of wind energy harvesting systems: a comparative analysis
• Chapter 10 : Human paradigm and reliability for aggregate production planning under uncertainty
• Chapter 11 : Artificial intelligence–based intelligent geospatial analysis in disaster management
• Chapter 12 : Optimizing the daily use of limited solar panels in closely located rural schools in Zimbabwe
• Chapter 13 : Review on recent implementations of multiobjective and multilevel optimization in sustainable energy economics
• Chapter 14 : Hybrid optimization and artificial intelligence applied to energy systems: a review
• Chapter 15 : A brief literature review of quantitative models for sustainable supply chain management
• Chapter 16 : Optimized designing spherical void structures in 3D domains
• Chapter 17 : Swarm-based intelligent strategies for charging plug-in hybrid electric vehicles
• Index
• A