Blockchain and Artificial Intelligence Technologies for Smart Energy Systems

Sun, Hongjian; Hua, Weiqi; You, Minglei

Abstract

Present energy systems are undergoing a radical transformation, driven by the urgent need to address the climate change crisis. At the same time, we are witnessing the sharp growth of energy data and a revolution of advanced technologies, with artificial intelligence (AI) and Blockchain emerging as two of the most transformative technologies of our time. The convergence of these two technologies has the potential to create a paradigm shift in the energy sector, enabling the development of smart energy systems that are more resilient, efficient, and sustainable. This book situates itself at the forefront of this paradigm shift, providing a timely and comprehensive guide to AI and Blockchain technologies in the energy system. Moving from an introduction to the basic concepts of smart energy systems, this book proceeds to examine the key challenges facing the energy system, and how AI and Blockchain can be used to address these challenges. Research examples are presented to showcase the role and impact of these new technologies, while the latest developed testbeds are summarised and explained to help researchers accelerate their development of these technologies. This book is an indispensable guide to the current changes in the energy system, being of particular use to industry professionals, from researchers to management, looking to stay ahead of technological developments.

Citation

Sun, H., Hua, W., & You, M. (2023). Blockchain and Artificial Intelligence Technologies for Smart Energy Systems. Chapman and Hall/CRC. https://doi.org/10.1201/9781003170440

• Book Type: Authored Book
• Online Publication Date: Oct 4, 2023
• Publication Date: 2023
• Deposit Date: Sep 28, 2023
• Publisher: Chapman and Hall/CRC
• Pages: 1-353
• Book Title: Blockchain and Artificial Intelligence Technologies for Smart Energy Systems
• ISBN: 9781000965544; 9780367771270
• DOI: https://doi.org/10.1201/9781003170440
• Keywords: Computer Science, Economics, Finance, Business & Industry, Engineering & Technology, Mathematics & Statistics
• Public URL: https://nottingham-repository.worktribe.com/output/25385794