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Elsevier

Smart Energy and Electric Power Systems

Current Trends and New Intelligent Perspectives

  • 1st Edition - September 17, 2022
  • Latest edition
  • Editors: Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen, Kayal Padmanandam, Rajesh Kumar Dhanaraj, Balamurugan Balusamy
  • Language: English

Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to… Read more

Description

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

Readership

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

  • Edition: 1
  • Latest edition
  • Published: September 17, 2022
  • Language: English

About the editors

SP

Sanjeevikumar Padmanaban

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.
Affiliations and expertise
Department of Electrical Engineering, Information Technology, and Cybernetics, University of South-Eastern Norway, Norway

JH

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

KP

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

RD

Rajesh Kumar Dhanaraj

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).
Affiliations and expertise
Professor, Symbiosis International (Deemed University), Pune, India

BB

Balamurugan Balusamy

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

Affiliations and expertise
Shiv Nadar University, Delhi-NCR, India

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