Digital Intelligence for Energy Systems

Innovation, Integration and Sustainability
Erscheinungsjahr 2026
ISBN: 978-981-9263-93-6
Verlag: Springer

Buch, Englisch, 360 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Mathematics for Sustainable Developments

This proceedings book contains select chapters on the integration of digital intelligence across the entire energy value chain, encompassing generation, transmission, distribution and end-use. Chapters are presented at the Second International Conference on Digital Intelligence for Energy Systems held at Innovation Campus, University of Wollongong, Australia, from 7 to 9 October 2026. Emphasizing sustainable applications, the book directly addresses topics related to SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation and Infrastructure), SDG 12 (Responsible Consumption and Production), SDG 13 (Climate Action) and SDG 17 (Partnerships for the Goals). Particular emphasis is placed on interdisciplinary approaches to the complex challenges of modern energy systems, including renewable integration, demand flexibility, smart grid operation and consumer engagement. 

Through a combination of theoretical studies, methodological developments and real-world case analyses, the book highlights the potential of digital intelligence to enhance efficiency, resilience and sustainability. Chapters showcase state-of-the-art research and practical applications that demonstrate how digital tools, such as advanced modelling, artificial intelligence, big data analytics and smart sensing, can transform energy system operation and planning. It also provides insights into policy, regulatory and market implications, underscoring the multidimensional nature of digital intelligence in energy transitions. The conference provided a global platform for academics, researchers, industry practitioners, government representatives and leaders of professional societies to present and discuss advances at the intersection of digital technologies and energy systems.

Zielgruppe

Research

Autoren/Hrsg.

Ma, Zhenjun

Shen, Jun

Xiao, Linda Fu

Sethuvenkatraman, Subbu

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Alternative und erneuerbare Energien
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Geistes- und Sozialwissenschaften
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Digital Intelligence-Driven Resilience Enhancement of Sustainable Distribution Energy Systems under Extreme Weather.- Spatio-Temporal Hybrid Mode Uncertainty Modeling Method for Power Systems Based on Aggregation-Decomposition.- Coordinated Control Method of Multi-Embedded DC Systems for Hybrid AC-DC Transmission Corridors.- Voltage Regulation of a Campus Distribution Network with High PV Penetration Using Flexible Resources.- Grid-Interactive Energy Flexibility for Controlled Environment Agriculture: A Case Study.- An Interpretable and Scalable Method for Evaluating Delivered Demand Response to Enable Grid Participation of Distributed Energy Resources.- Ex-Ante Predictability Diagnosis for High-Error Screening in Day-Ahead Multi-Energy Load Forecasting.- An LLMs-Driven Semantic Construction Method for Automated and Interpretable Anomaly Detection in Building Energy Systems.- A Residual-Adaptive Threshold Coupling Mechanism Framework for Hierarchical Uncertainty Quantification and Load Interval Prediction of Pumping Unit Systems.- A Framework for Applying Fault Propagation Graphs to Automated Fault Detection and Diagnosis.- Short-Term Air Conditioning Cooling Load Prediction for Metro Station Equipment Rooms Using a Convolutional Neural Network.- Evaluating Energy Retrofit in Social Housing.- Load Shifting or Shedding? Impact of Heating Emission System and Thermal Storage in a Danish Residential Building.- Reliability Impacts of Using Commercial Building Power Supply Systems.- Digital Twin-Based Commissioning of a Chilled Water System for an Intelligent Lithium-Ion Battery Factory.- A Skill-Oriented Multimodal LLM Architecture for Topology and Parametric HVAC Simulation Model Generation.

Über Autor(innen)

Zhenjun Ma is Professor and Director of the Sustainable Buildings Research Centre at the University of Wollongong, Australia. His research covers digital technologies, distributed energy, thermal storage and demand flexibility in buildings. He has led numerous projects aimed at decarbonising the built environment and integrating buildings into low-carbon energy systems. He is Associate Editor of the and serves on editorial boards of , Sustainable Energy Technologies and Assessments, and , Part A, journals. He is also Managing Editor of Springer’s . His awards include fellowships from JSPS and the Australian Government, an Innovation Award from the World Society of Sustainable Energy Technologies and two HVAC&R Research Awards from AIRAH. He plays a key role in global collaborations, especially through IEA-EBC Annexes on demand flexibility.

Jun Shen is Full Professor in the School of Computing and Information Technology at the University of Wollongong, Australia, where he has previously served as Head of Postgraduate Studies and Chair of the School Research Committee. He is Senior Member of IEEE, ACM and ACS and is also IEEE Distinguished Lecturer. He has authored over 480 publications in leading journals and conferences across computer science and information technology. His research expertise spans computational intelligence, bioinformatics, cloud computing and learning technologies, including MOOCs. He has served as Editor, Program Committee Chair, Guest Editor and Program Committee Member for numerous journals and conferences published by IEEE, ACM, Elsevier and Springer. Professor Shen was also Member of the ACM/AIS Task Force on Curriculum MSIS 2016. His work has appeared in highly ranked journals, including  , more than 20 different .

Linda Fu Xiao is Professor and Associate Dean at the Faculty of Construction and Environment, The Hong Kong Polytechnic University. She is a Fellow of ASHRAE and IBPSA. Her research focuses on smart buildings and energy system management, with expertise in dynamic modelling, optimal control, diagnostics, and applying AI and big data for energy-efficient, resilient buildings. She has received numerous awards, including the Dean’s Award for Outstanding Achievement in Research Funding,  President’s Award for Knowledge Transfer,  ASHRAE Technology Award and multiple best paper honours. Prof. Xiao is Associate Editor of and Subject Editor of . Her work has been widely adopted in both new and existing buildings, delivering substantial energy savings.

Dr Subbu Sethuvenkatraman is an Honorary Professor at the University of Wollongong and a researcher at CSIRO’s Energy division, with more than 25 years of experience in clean energy research and development, he has led the development of innovative energy solutions with a particular emphasis on digital technologies and data-driven approaches. His current research focuses on ways to integrate distributed energy resources within buildings into the electricity grid, enabling building-to-grid interactions and supporting the transition to a net-zero energy system. He has extensive expertise in building energy performance, demand flexibility, smart energy systems, and digital infrastructure for the built environment. Dr Sethuvenkatraman serves as an Associate Editor of the ASME Journal of Engineering for Sustainable Buildings and Cities and is the Co-Operating Agent for the International Energy Agency (IEA) Energy in Buildings and Communities (EBC) Annex 96: Grid-Integrated Control of Buildings, an international research collaboration focused on enabling buildings to operate as flexible, grid-responsive energy assets.