Smart Energy and Electric Power Systems

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.

Padmanaban Sanjeevikumar is a Full Professor in Electrical Power Engineering with the Department of Electrical Engineering, Information Technology, and Cybernetics, University of South-Eastern Norway, Norway. He has over a decade of academic and teaching experience, including Associate/Assistant Professorships at the University of Johannesburg, South Africa (2016-2018), Aalborg University, Denmark (2018-2021) and the CTIF Global Capsule Laboratory at Aarhus University, Denmark (2021-present). Prof. Sanjeevikumar received a lifetime achievement award from Marquis Who’s Who - USA 2017 for contributing to power electronics and renewable energy research, and was listed among the world’s top 2% of scientists by Stanford University, USA in 2019. 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 in the School of Computing Science and Engineering at Galgotias University, Greater Noida, India. He received the B.E. degree in Computer Science and Engineering from the Anna University Chennai, India in 2007 and the M.Tech from the Anna University Coimbatore, India in 2010 and Ph.D. degree in Computer Science from Anna University, Chennai, India, in 2017. He has contributed 40+ Authored and Edited books on various technologies, 21 Patents and 70+ articles and papers in various refereed journals and international conferences and contributed chapters to the books. His research interests include Machine Learning, Cyber-Physical Systems and Wireless Sensor Networks. He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), member of the Computer Science Teacher Association (CSTA); and International Association of Engineers (IAENG). He is serving as an Associate Editor and Guest Editor for reputed journals Elsevier Computers and Electrical Engineering, Human-centric Computing and Information Sciences, Emerald - International Journal of Pervasive Computing and Communications, Hindawi - Mobile Information Systems, etc. He is an Expert Advisory Panel Member of Texas Instruments Inc., USA. Dr. Balamurugan Balusamy is Associate Dean at Shiv Nadar University, Delhi, India. Prior to this, Dr. Balusamy was a Professor in the School of Computing Sciences and Engineering and Direc