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Cited by 233Microgrid Control and OptimizationDigital Transformation in IndustryReal-time simulation and control systems

Microgrid Digital Twins: Concepts, Applications, and Future Trends

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Bazmohammadi, Najmeh, Madary, Ahmad, Vasquez, Juan C., Mohammadi, Hamid Baz, Khan, Baseem, Wu, Ying, Guerrero, Josep M.·2022·IEEE Access
DOI 10.1109/access.2021.3138990
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Abstract

Following the fourth industrial revolution, and with the recent advances in information and communication technologies, thedigital twinningconcept is attracting the attention of both academia and industry worldwide. A microgrid digital twin (MGDT) refers to the digital representation of a microgrid (MG), which mirrors the behavior of its physical counterpart by using high-fidelity models and simulation platforms as well as real-time bi-directional data exchange with the real twin. With the massive deployment of sensor networks and IoT technologies in MGs, a huge volume of data is continuously generated, which contains valuable information to enhance the performance of MGs. MGDTs provide a powerful tool to manage the huge historical data and real-time data stream in an efficient and secure manner and support MGs’ operation by assisting in their design, operation management, and maintenance. In this paper, the concept of the digital twin (DT) and its key characteristics are introduced. Moreover, a workflow for establishing MGDTs is presented. The goal is to explore different applications of DTs in MGs, namely in design, control, operator training, forecasting, fault diagnosis, expansion planning, and policy-making. Besides, an up-to-date overview of studies that applied the DT concept to power systems and specifically MGs is provided. Considering the significance of situational awareness, security, and resilient operation for MGs, their potential enhancement in light of digital twinning is thoroughly analyzed and a conceptual model for resilient operation management of MGs is presented. Finally, future trends in MGDTs are discussed.

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  96. NAJMEH BAZMOHAMMADI (Member, IEEE) received the B.Sc. degree in electrical engineer- ing and the M.Sc. degree in electrical engineering (control theory) from the Ferdowsi University of Mashhad, Iran, in 2009 and 2012, respectively, and the Ph.D. degree in electrical engineering (con- trol theory) from the K. N. Toosi University of Technology, Tehran, Iran, in 2019. She is cur- rently a Postdoctoral Fellow with the Center for Research on Microgrids (CROM), AAU Energy, Aalborg University, Denmark. Her current research interests include digi- tal twins, modeling and control of dynamic systems, optimization, model predictive control, and its application in energy management of hybrid and renewable-based power systems and life support systems.

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Authors
Bazmohammadi, N., Madary, A., Vasquez, J. C., Mohammadi, H. B., Khan, B., Wu, Y., & Guerrero, J. M.
Affiliations
  • Aalborg University (DK)
  • Aarhus University (DK)
  • Telus (Canada) (CA)
  • Hawassa University (ET)
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2022
Volume
10
Pages
2284-2302
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2021.3138990
OpenAlex
W4206739815
Cited by
233
References
13
Citations by year
2026: 49 · 2025: 61 · 2024: 58 · 2023: 47 · 2022: 18
FWCI
13.69
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Access (publishedVersion, cc-by)
  • VBN Forskningsportal (Aalborg Universitet) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
VILLUM FONDEN under the VILLUM Investigator Grant (25920): Center for Research on Microgrids
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Microgrid Control and Optimization
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
  • Physical Sciences › Engineering › Control and Systems Engineering › Real-time simulation and control systems
Keywords
digital twin, microgrids, real-time data exchange, sensor networks, Internet of Things, operator training, fault diagnosis, forecasting, expansion planning, policy making, situational awareness

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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