Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies

Krishna Kumar, Ram Shringar Rao, Omprakash Kaiwartya, Shamim Kaiser, Sanjeevikumar Padmanaban

• Publisher: Elsevier
• Year: 2022
• ISBN:
  9780323914284
• Topic: Technology & Engineering
• Subtopic: Renewable Power Resources
• Index: Technology & Engineering

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development.

As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation.

• Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment
• Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum
• Addresses the advanced field of renewable generation, from research, impact and idea development of new applications

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Dedication
• Contributors
• About the editors
• Preface
• Chapter 1: Application of alternative clean energy
• Chapter 2: Optimization of hybrid energy generation
• Chapter 3: IoET-SG: Integrating internet of energy things with smart grid
• Chapter 4: Evolution of high efficiency passivated emitter and rear contact (PERC) solar cells
• Chapter 5: Online-based approach for frequency control of microgrid using biologically inspired intelligent controller
• Chapter 6: Optimal allocation of renewable energy sources in electrical distribution systems based on technical and economic indices
• Chapter 7: Optimization of renewable energy sources using emerging computational techniques
• Chapter 8: Advanced renewable dispatch with machine learning-based hybrid demand-side controller: The state of the art and a novel approach
• Chapter 9: A machine learning-based design approach on PCMs-PV systems with multilevel scenario uncertainty
• Chapter 10: Agent-based peer-to-peer energy trading between prosumers and consumers with cost-benefit business models
• Chapter 11: Machine learning-based hybrid demand-side controller for renewable energy management
• Chapter 12: Prediction of energy generation target of hydropower plants using artificial neural networks
• Chapter 13: Response surface methodology-based optimization of parameters for biodiesel production
• Chapter 14: Reservoir simulation model for the design of irrigation projects
• Chapter 15: Effect of hydrofoils on the starting torque characteristics of the Darrieus hydrokinetic turbine
• Index