Smart Energy and Electric Power Systems

Smart Energy and Electric Power Systems

Current Trends and New Intelligent Perspectives

1st Edition - September 1, 2022

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  • Editors: Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen, Kayal Padmanandam, Rajesh Dhanaraj, Balamurugan Balusamy
  • Paperback ISBN: 9780323916646

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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.

Key Features

  • 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


Early career researchers focusing on machine learning, energy grid applications, and system design for smart grids; Professionals in the energy sector, researchers and application developers of machine learning and artificial intelligence-based smart grid solutions

Table of Contents

  • 1. Introduction: Artificial intelligence and Smart Power Systems
    2. Integrated Architecture of Machine Learning and Smart Power System
    3. Challenges and issues in Power Systems
    4. Load shedding and related techniques to solve the power crisis
    5. ML in distributed energy resources and prosumers market
    6. ML-based electricity demand prediction
    7. Applying ML to determine the power outage
    8. Predictive and Prescriptive analytics for component fault detection
    9. Balancing demand and supply of electricity with machine learning
    10. Preventive care of grid hardware with anomaly detection
    11. AI-based Smart feeder monitoring system
    12. Algorithms for buss loss and reliability indices calculations
    13. ML-based security solutions to protect smart power systems
    14. Cyber-attacks ,security data detection, and critical loads in the power systems
    15. Integration of AI/ML into the energy sector: Case Studies

Product details

  • No. of pages: 296
  • Language: English
  • Copyright: © Elsevier 2022
  • Published: September 1, 2022
  • Imprint: Elsevier
  • Paperback ISBN: 9780323916646

About the Editors

Sanjeevikumar Padmanaban

Sanjeevikumar Padmanaban (Member'12, Senior Member'15 IEEE) received a bachelor's degree from the University of Madras, India in 2002, a master's degree (Hons.) from Pondicherry University, India in 2006, and a Ph.D. from the University of Bologna, Italy in 2012. He was an associate in various institutions like VIT University India, National Institute of Technology, India, Qatar University, Qatar, Dublin Institute of Technology, Ireland, and the University of Johannesburg, South Africa. He is currently working as a faculty member with the Department of Business Development and Technology, Aarhus University, Denmark. He has authored more than 300 scientific papers and has received the Best Paper cum Most Excellent Research Paper Award from IET-SEISCON’13, IET-CEAT’16, and five best paper awards from ETAEERE’16. He is a fellow of the Institution of Engineers, FIE, India, a fellow of the Institution of Telecommunication and Electronics Engineers, FIETE, India, and a fellow of the Institution of Engineering and Technology, IET, UK. He serves as an Editor/Associate Editor/Editorial Board of refereed journals, in particular, the IEEE Systems Journal, the IEEE Access Journal, the IET Power Electronics, Journal of Power Electronics, Korea, and as a subject editor of the IET Renewable Power Generation, IET Generation, Transmission and Distribution, and of FACTS Journal, Canada.

Affiliations and Expertise

CTiF Global Capsule (CGC), Department of Business Development and Technology, Aarhus University, Herning, Denmark

Jens Bo Holm-Nielsen

Dr Jens Bo Holm-Nielsen is Associate Professor and Head of Center for Bioenergy and Green Engineering, Aalborg University, Aalborg, Denmark

Affiliations and Expertise

Associate Professor and Head, Center for Bioenergy and Green Engineering, Aalborg University, Aalborg, Denmark

Kayal Padmanandam

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.

Affiliations and Expertise

Associate Professor, Department of Information Technology and Member of the Research and Development Cell, BVRITH College of Engineering, Hyderabad, India

Rajesh Dhanaraj

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 25+ Authored and Edited books on various technologies, 21 Patents and 53 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 an Expert Advisory Panel Member of Texas Instruments Inc USA.

Affiliations and Expertise

Associate Professor, School of Computing Science and Engineering, Galgotias University, Greater Noida, U.P, India

Balamurugan Balusamy

Balamurugan Balusamy is currently working as an Associate Dean Student in Shiv Nadar University, Delhi-NCR. Prior to this assignment, he was a Professor in the School of Computing Sciences & Engineering and Director International Relations at Galgotias University, Greater Noida, India. His contributions focuses on Engineering Education, Block chain and Data Sciences. His Academic degrees and twelve years of experience working as a Faculty in a global University like VIT University, Vellore has made him more receptive and prominent in his domain. He does have 200 plus high impact factor papers in Springer, Elsevier and IEEE. He has done more than 80 Edited and authored books and collaborated with eminent professors across the world from top QS ranked university. Prof. Balamurugan Balusamy has served up to the position of Associate Professor in his stint of 12 years of experience with VIT University, Vellore. He had completed his Bachelors, Masters and PhD Degrees from Top premier institutions from India. His passion is teaching and adapts different design thinking principles while delivering his lectures. He has published 80+ books on various technologies and visited 15 plus countries for his technical course. He has several top-notch conferences in his resume and has published over 200 of quality journal, conference and book chapters combined. He serves in the advisory committee for several startups and forums and does consultancy work for industry on Industrial IOT. He has given over 195 talks in various events and symposium.

Affiliations and Expertise

Associate Dean-Student Engagement, Shiv Nadar University, Delhi-National Capital Region (NCR)

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