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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Request a sales quoteDigital 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.
- Provides a clear grounding in the fundamentals of DTT and opportunities for this innovative method in the energy industry
- Guides students and industry practitioners step-by-step from the discovery of techniques to practical model building
- Includes examples and case studies presented by a range of global experts
- Led by an experienced editorial team of educators and industry professionals
Undergraduate and postgraduate students, researchers, and engineers.Energy industries and energy stakeholders, energy policy makers
- 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
- No. of pages: 300
- Language: English
- Edition: 1
- Published: November 13, 2024
- Imprint: Elsevier
- Paperback ISBN: 9780443140709
- eBook ISBN: 9780443140716
MA
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, GermanyAM
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, NorwayGL
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), NorwayUC
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 KingdomRead Digital Twin Technology for the Energy Sector on ScienceDirect