Digital Twin Technology for the Energy Sector

Fundamentals, Advances, Challenges, and Applications

1st Edition - November 13, 2024
Editors: Mohammadreza Aghaei, Amin Moazami, Gabriele Lobaccaro, Umit Cali
Language: English
Paperback ISBN:
9 7 8 - 0 - 4 4 3 - 1 4 0 7 0 - 9
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 1 4 0 7 1 - 6

Digital Twin Technology for the Energy Sector: Fundamental, Advances, Challenges, and Applications introduces the energy sector to this innovative technology and its potential… Read more

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Digital Twin Technology for the Energy Sector: Fundamental, Advances, Challenges, and Applications introduces the energy sector to this innovative technology and its potential for supporting energy transition. The book outlines the fundamentals of digital twin technology (DTT), giving readers a thorough grounding in its theory and use. Additional chapters provide practical, real-world options for applying the technology in a variety of energy sectors, from wind, solar, and hydropower, to the electrical industry and mobility. Its potential uses for energy flexibility, managing supply and demand in electric grids, and energy modeling in real time are also given significant attention.

Including insights from a wide range of expert researchers and industry professionals, this book will guide readers from their first steps in DTT to developing innovative applications for the energy sector of the future.

Title of Book
Cover image
Title page
Table of Contents
Copyright
Dedication
List of contributors
About the editors
Foreword
Preface
Acknowledgments
Reviewers
Chapter 1. Introduction to emerging technologies for acceleratingthe energy transition
Abstract
1.1 Introduction
1.2 Energy transition: overview and importance
1.3 Emerging technologies in energy transition
1.4 Renewable energy technologies
1.5 Energy storage technologies
1.6 Smart grid and grid integration technologies
1.7 Electrification and decentralization
1.8 Conclusions, lessons learned, and future perspectives
Acknowledgment
References
Chapter 2. Digital twin technology: fundamental aspects and advances
Abstract
2.1 Introduction
2.2 Definition and typology
2.3 Fundamental aspects of digital twins
2.4 Classification of digital representation
2.5 Digital model
2.6 Digital shadow
2.7 Digital twin
2.8 Conclusions
Acknowledgments
AI disclosure
References
Chapter 3. Cybersecurity, digital privacy, and modeling aspects of digital twins
Abstract
3.1 Introduction
3.2 System modeling framework
3.3 Digital twins under the context of cybersecurity and privacy considerations
3.4 Frameworks and assessment models
3.5 Use-cases
Appendix A: Operationalizing the artificial intelligence trust framework and maturity model
Appendix B: A deep-dive on Security goals pertinent to SAIF
References
Chapter 4. Digital twin technology in the electrical power industry
Abstract
4.1 Introduction
4.2 Related works
4.3 Digital twin architecture
4.4 Methodologies and enabling technologies
4.5 Digital twin applications
4.6 Case studies
4.7 Conclusion
Acknowledgment
References
Chapter 5. Digital twin technology in microgrid systems
Abstract
5.1 Introduction
5.2 Related works
5.3 Digital twin architecture in microgrid systems
5.4 Digital twin applications for microgrid components
5.5 Digital twin applications in microgrid systems
5.6 Conclusion
Acknowledgment
References
Chapter 6. Digital twin in design and control optimization of marine renewable energy and offshore wind energy systems
Abstract
6.1 Introduction
6.2 Foundations of marine renewable energy systems
6.3 Design, Control, and optimization aspects of marine renewable and offshore wind energy systems
6.4 Digital twin engineering for marine renewable energy systems
6.5 Digital twin industrial, educational, and work safety aspects
6.6 Conclusion and future work
References
Chapter 7. Simulation and visualization aspects of a digital twin for wind farms
Abstract
7.1 Introduction to cosimulation and model exchange
7.2 Standards, tools, and frameworks supporting cosimulation and/or model exchange
7.3 Combining frameworks and standards
7.4 Wind turbine cosimulation use case
AI disclosure
References
Chapter 8. Enhancing wind farm energy prediction through digital twin integration
Abstract
8.1 Introduction
8.2 The role of digital twins in wind energy
8.3 Prediction of energy production in wind farms
8.4 Digital twin implementation and case studies
8.5 Benefits and challenges
AI disclosure
References
Chapter 9. Digital twin technology in solar energy
Abstract
9.1 Introduction to digital twin technology in solar energy
9.2 Application of digital twin for solar plants
9.3 Data collection and analysis for digital twins in solar energy
9.4 Challenges and opportunities for digital twin technology in solar energy
9.5 Conclusion
Acknowledgment
Disclosure
References
Chapter 10. Digital twins for hydropower applications
Abstract
10.1 Introduction
10.2 Hydroelectric power plants
10.3 Digital twin in Hydroelectric power generation
10.4 Summary
Acknowledgement
References
Chapter 11. Digital twin technology for energy flexibility and saving
Abstract
11.1 Introduction
11.2 Digital twins for buildings
11.3 Conclusions and lessons learned
References
Chapter 12. Electric mobility and beyond: advancing charging infrastructure optimization with digital twins
Abstract
12.1 Introduction
12.2 Digital twin and artificial intelligence for electric vehicles
12.3 Digital twin of charging station
12.4 Enhancing electric vehicle charging infrastructure through digital twin and parallel intelligence
12.5 Conclusions
AI disclosure
References
Index

Mohammadreza Aghaei

Mohammadreza Aghaei is a distinguished senior researcher and Professor with more than 18 years of experience and expertise spanning multidisciplinary fields, including energy transition, energy systems integration, renewables, solar photovoltaics, smart buildings and grids, as well as smart technologies such as artificial intelligence, Internet of Things, digital twin, unmanned aerial vehicles, autonomous control systems, and intelligent monitoring. His extensive academic journey includes affiliations with prestigious institutions such as Politecnico di Milano, Fraunhofer ISE, Helmholtz- Zentrum Berlin, Eindhoven University of Technology, University of Freiburg, and Norwegian University of Science and Technology. Throughout his career, Professor Aghaei has been actively engaged in numerous national and EU-funded research projects, showcasing his commitment to advancing knowledge and innovation in the field. Presently, he serves as the Coordinator of the EU Horizon 2020 project “COLLECTiEF” - Collective Intelligence for Energy Flexibility, demonstrating his leadership and expertise in spearheading large-scale initiatives. A senior member of IEEE, he has authored more than 150 publications in internationally refereed journals, book chapters, and conference proceedings. His contributions have significantly impacted the academic community and the broader field of energy research, cementing his reputation as a leading authority in the domain.

Affiliations and expertise

Senior Scientist, Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway Professor, Department of Sustainable Systems Engineering (INATECH), Solar Energy Engineering program, University of Freiburg, Germany

Amin Moazami

Amin Moazami is a pioneering researcher in smart buildings and energy flexibility and application of distributed intelligence (swarm intelligence, collective intelligence, and multiagent systems) for energy management. He is a Research Manager in Sintef. He was also appointed as an Associate Professor in the Department of Ocean Operations and Civil Engineering at NTNU and as the Head of the Energy Management and Efficiency Research Group (EMERGE). He has strong experience in building performance simulation, energy flexibility, climate robustness and resilience in buildings, occupant behavior, and so on. He was the Coordinator of COLLECTiEF project and was actively involved in several national and international projects. In 2019, he has been awarded an innovation grant (innovasjonsstipend, 2019) for the proposal “A simulation-based tool for development of Collective Intelligence (CI) at urban scale to mitigate the impacts of extreme climate conditions,” focusing on developing a new solution for increasing the energy demand flexibility of urban areas.

Affiliations and expertise

Research Manager, Department of Architectural Engineering, Sintef Community; Associate Professor, Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway

Gabriele Lobaccaro

Gabriele is an emerging researcher in renewable energy, with a focus on the digitalization of solar energy in the built environment. His background is grounded on building engineer and architecture knowledge and his expertise convers solar energy systems integration at building and district level, urban energy planning, smart cities, climate-based solutions, mitigation, and adaptation strategies, and environmental, microclimate, and energy analyses. He is contributing to advance the state-of-the-art of solar energy exploration and integration through the definition of solar neighborhoods’ archetypes, approaches, methods, and tools to accelerate the use of solar energy in built environments. Gabriele coordinated the Subtask C “Case studies and action research” in the IEA Task 51 Solar Energy in Urban Planning and now he is coordinating the Subtask D “Case studies” in the IEA Task 63 Solar Neighbourhood Planning and the activity A3 - BIPV in our society within IEA PVPS Task 15 - Enabling Framework for the Development of BIPV. Gabriele has experienced in several national (REINVENT and HELIOS), European (Exploit4InnoMat, RAMSES, and CoSSMic), and international research projects (SEniC, SiNoPSE, and iSTAR). Gabriele has co-/ author of more than 65 publications, including research and review articles in international high-impact peer-reviewed journals, national and international conference proceedings, book chapters, and books.

Affiliations and expertise

Associate Professor, Department of Civil and Environmental Engineering, Norwegian University of Science and Technology (NTNU), Norway

Umit Cali

Professor Umit Cali is a distinguished technology researcher with more than 20 years of global experience in IT law, energy systems, blockchain, and data science. His career includes impactful roles such as Network Engineer at IBM International, Senior Researcher at the Fraunhofer Institute, and CTO for KREEN Renewables GmbH. Currently, he is a Professor and Chair in digital engineering at the University of York and a Part-Time Professor of energy informatics at NTNU. Umit pioneered merging technology with social systems, notably in artificial intelligence, digital privacy, cyber law, and blockchain. He led IEEE groups on these fronts and founded startups in the United States and Switzerland focusing on digital solutions for the energy sector. He holds three patents, has authored books on digital energy sector transformation, and is enhancing his expertise with an LLM in digital law at the University of Go¨ttingen, expected by May 2024. His journey began with an Electrical Engineering degree from Yildiz Technical University and a PhD from the University of Kassel in Germany.

Affiliations and expertise

Professor, Digital Engineering for Future Technologies, University of York, United Kingdom

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Digital Twin Technology for the Energy Sector

Fundamentals, Advances, Challenges, and Applications

Purchase options

Save 50% on book bundles

Institutional subscription on ScienceDirect

Mohammadreza Aghaei

Amin Moazami

Gabriele Lobaccaro

Umit Cali