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Expected by: 01 December 2026
AI Explainability and Governance in Smart Energy Systems
Artificial intelligence may have the potential to deliver more efficient, reliable and sustainable energy systems, particularly by helping to manage the complexity of distributed generation and demand-side management. However, stakeholders expect interpretability and explainability, and AI tools must also be transparent, secure and trustworthy. Explainable AI (XAI) models are intended to make AI algorithms more transparent and understandable without reducing their performance and efficiency.
When AI is used in the energy sector, evaluating huge and complex datasets and making decisions to predict generation or consumption patterns, to help controlling voltage and frequency, or to control wind turbines and solar systems, owners and operators need to know and trust the algorithms to be willing to relinquish control of their assets to them.
AI Explainability and Governance in Smart Energy Systems is a comprehensive reference, written by an international team of experts. Chapters cover AI explainability in energy systems, integrated forecasting of generation and load, energy storage, integration of IoT and edge computing, AI explainability with blockchain, AI-driven energy markets, policy, and governance, case studies, human-AI collaboration, climate resilience, ethical and social implications, ethical considerations and future perspectives.
The book is intended for an audience of academic researchers in smart energy technology and XAI, energy markets and energy management, as well as for advanced students in energy systems-related subjects.
About the Editors
Pushpalatha Naveenkumar is an associate professor in the Department of Electrical and Electronics Engineering at Sri Eshwar College of Engineering, India. A lifetime member of ISTE and IETE, she has served as a technical program committee member, session chair, and reviewer for national and international conferences. She has authored over 40 research articles, published 14 patents, and served as a project evaluator for Toycathon 2021. Her research focuses on AI applications in energy systems, batteries, and electric vehicle charging.
Balamurugan Balusamy is professor and chairperson of the School of Engineering and IT at Manipal University Dubai. Recognized among Stanford University's Top 2% Scientists Worldwide (2023) in Data Science/AI/ML, his research spans engineering education, blockchain, and data science. He has published over 200 journal papers and authored or edited more than 200 books. An active international academic leader, he has delivered over 210 invited talks and organized numerous IEEE and ACM conferences.
Firoz Khan is an assistant professor in the Center for Information and Communication Sciences at Ball State University, USA. His primary research focuses on network security, information assurance, and cybersecurity, with additional interests in machine learning applications for data analytics and big data. He teaches courses in computer and network security, ethical hacking, digital forensics, and cybersecurity. His work emphasizes developing secure and resilient systems capable of withstanding evolving cyber threats and attacks.
Sumendra Yogarayan is an assistant professor and deputy dean (postgraduate and collaborations) at the Faculty of Information Science and Technology, Multimedia University, Malaysia. He earned his PhD in Information Technology from Multimedia University in 2023 and is a registered professional technologist (Ts.) with MBOT. His research and teaching interests include intelligent transportation systems, wireless communications, ad hoc networks, machine learning, the internet of things, embedded systems, and sensor technologies.
Rose Bindu Joseph P is an assistant professor in the Department of Mathematics at Dayananda Sagar College of Engineering, Bengaluru, India. She has published more than 20 research papers, contributed book chapters, and holds two published patent applications. Her research interests include fuzzy theory, soft computing, computer vision, biometrics, and data analytics. She actively explores the application of computational intelligence techniques to solve complex real-world problems across interdisciplinary domains.
Publication Year:
2026
Pages:
370
ISBN-13: 978-1-83724-401-0
Format:
HBK
Editors:
Pushpalatha Naveenkumar, Balamurugan Balusamy, Firoz Khan, Sumendra Yogarayan, Rose Bindu Joseph