A survey of Digital Twin techniques in smart manufacturing and management of energy applications
Open accessAbstract
With the continuous advancement and exploration of science and technology, the future trend of energy technology will be the deep integration of digitization, networking, intelligence with energy applications. The increasing maturity of digital technologies, such as the Internet of Things, big data, and cloud computing, has given rise to the creation and use of a potential technology – Digital Twin. Currently, research on Digital Twin has produced many concepts and outcomes that have been applied in many fields. In the energy sector, while some relevant ideas and case studies of Digital Twin have been generated, there are still many gaps to be explored. As a potential technology with advantages in many aspects, Digital Twin is bound to generate more promotion and applications in the energy fields. This paper systematically reviews the existing Digital Twin approaches and their possible applications in the energy fields. In addition, this paper attempts to analyze Digital Twin from different perspectives, such as definitions, classifications, main features, case studies and key technologies. Finally, the directions and challenges of possible future applications of Digital Twin in the energy fields have been presented.
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DTs in smart energy applications are generally classified into four key levels: lowcarbon cities, smart grids, electrified transportation, and advanced energy storage systems.
“DTs in smart energy applications are generally classified into four key levels: lowcarbon cities, smart grids, electrified transportation, and advanced energy storage systems [115].”
From Analysis of Digital Twin Applications in Energy Efficiency: A Systematic Review (2025) · cites this paper as [115]
Cites
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Analysis of Digital Twin Applications in Energy Efficiency: A Systematic Review
Ba, L., Tangour, F., El Abbassi, I., & Absi, R. (2025) · Sustainability · doi:10.3390/su17083560 · Cited by 96 · see citing works
- Authors
- Wang, Y., Kang, X., & Chen, Z.
- Affiliations
- University of Science and Technology of China (CN)
- Corresponding author
- Wang, Yujie
- Venue
- Green Energy and Intelligent Transportation
- Publisher
- Elsevier BV
- Published
- 2022-09
- Volume
- 1
- Issue
- 2
- Pages
- 100014
- ISSN
- 2773-1537 (ISSN-L)
- OpenAlex
- W4283330583
- Cited by
- 147
- References
- 6
- Citations by year
- 2026: 28 · 2025: 31 · 2024: 36 · 2023: 44 · 2022: 8
- FWCI
- 13.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Green Energy and Intelligent Transportation (publishedVersion, cc-by-nc-nd)
- Funders
- National Key Research and Development Program of China (2020YFB1712400)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Energy, Economy, and Technology Trends
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Keywords
- digital twin, smart manufacturing, energy management, energy applications, Internet of Things, big data, cloud computing, digital twin definition
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