Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing.
Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector.
- Helps improve the prediction capability of AI algorithms to make evidence-based decisions in the smart supply of electricity, including load shedding
- Focuses on how to integrate AI and ML into the energy sector in the real-world, with many chapters accompanied by case studies
- Addresses a number of proven AI and ML- informed techniques in rebalancing supply and demand
Prof. Sanjeevikumar Padmanaban is a full professor of electrical power engineering in the Department of Electrical Engineering, Information Technology, and Cybernetics, at the University of South-Eastern Norway. He received his PhD in electrical engineering from the University of Bologna, Italy, in 2012. Subsequently, he held positions at VIT University (India), National Institute of Technology (India), Qatar University, Dublin Institute of Technology (Ireland), University of Johannesburg (South Africa), Aalborg University (Denmark), and Aarhus University (Denmark). Prof. Padmanaban has authored over 750 scientific papers and has been listed among the world’s top 2% of scientists (from 2019) by Stanford University. He is editor, associate editor, or editorial board member for several important refereed journals, and a Fellow of the Institution of Engineers, India, the Institution of Electronics and Telecommunication Engineers, India, and the Institution of Engineering and Technology, U.K. He received a lifetime achievement award from Marquis Who’s Who–USA 2017 for his contributions to power electronics and renewable energy research.
Dr Jens Bo Holm-Nielsen is Associate Professor and Head of Center for Bioenergy and Green Engineering, Aalborg University, Aalborg, Denmark
Dr.Kayal Padmanandam has over a decade of credentials in the domain of Computer Science with wide exposure through teaching, research, and industry. She is passionate about research and specialized in Data Science and Machine Learning Algorithms in which she pursued her doctoral research. She has several publications especially related to machine-learning applications. She is a post-graduate/graduate educator for Engineering and Science scholars. Currently, she is working as an Associate Professor in the Department of Information Technology and as a Member of the Research & Development Cell, BVRITH College of Engineering, Hyderabad, India.
Dr. Rajesh Kumar Dhanaraj is a professor at the Symbiosis International (Deemed University) in Pune, India. His research and publication interests include cyber-physical systems, wireless sensor networks, and cloud computing. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), a member of the Computer Science Teacher Association (CSTA) and member of the International Association of Engineers (IAENG). He is an expert advisory panel member of Texas Instruments Inc. (USA), and an associate editor of
International Journal of Pervasive Computing and Communications (Emerald Publishing).
Dr. Balamurugan Balusamy is currently working as an Associate Dean Student in Shiv Nadar Institution of Eminence, Delhi-NCR. He is part of the Top 2% Scientists Worldwide 2023 by Stanford University in the area of Data Science/AI/ML. He is also an Adjunct Professor in the Department of Computer Science and Information Engineering, Taylor University, Malaysia. His contributions focus on engineering education, blockchain, and data sciences
