Survey Paper of Digital Twins and their Integration into Electric Power Systems

Nguyen, Sabrina; Abdelhakim, Mai; Kerestes, Robert J.

doi:10.1109/pesgm46819.2021.9638011

Cited by 14 publications

(3 citation statements)

References 20 publications

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“…Existing surveys addressing the DT field focus on characterizing DTs from modeling perspectives, architecture proposals, and the categories of services and applications most used in a field. Readers are referred to surveys that deal with foundation concepts of DTs [11]- [18]; industry verticals [19]- [22] and also in Industry 4.0 manufacturing models [23]; civil engineering [24]- [29]; agriculture [30]- [32]; energy [33]- [36]; healthcare [37], [38]; and, finally, to smart cities [39], [40]. Although DTs have been gaining popularity in transport system solutions, a survey that updates the state of the art of DTs for ITS is yet to be found in the literature.…”

Section: B Contributions and Organizationmentioning

confidence: 99%

Sustainable Intelligent Transportation Systems via Digital Twins: A Contextualized Survey

Martínez,

Campelo,

Ribeiro

2024

Preprint

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Section: B Contributions and Organizationmentioning

confidence: 99%

Sustainable Intelligent Transportation Systems via Digital Twins: A Contextualized Survey

Martínez,

Campelo,

Ribeiro

2024

Preprint

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“…Figure 3 presents an overview of the evolutionary history of DTs. The development of DT technology can be categorized into four stages: the pre-DT stage, the DT stage, the adaptive DT stage, and the smart DT stage [43]. Figure 3 presents an overview of the evolutionary history of DTs.…”

Section: Development and Evolution Of Dtmentioning

confidence: 99%

Emerging Information Technologies for the Energy Management of Onboard Microgrids in Transportation Applications

Huang,

Xiao,

Gao

et al. 2023

Energies

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The global objective of achieving net-zero emissions drives a significant electrified trend by replacing fuel-mechanical systems with onboard microgrid (OBMG) systems for transportation applications. Energy management strategies (EMS) for OBMG systems require complicated optimization algorithms and high computation capabilities, while traditional control techniques may not meet these requirements. Driven by the ability to achieve intelligent decision-making by exploring data, artificial intelligence (AI) and digital twins (DT) have gained much interest within the transportation sector. Currently, research on EMS for OBMGs primarily focuses on AI technology, while overlooking the DT. This article provides a comprehensive overview of both information technology, particularly elucidating the role of DT technology. The evaluation and analysis of those emerging information technologies are explicitly summarized. Moreover, this article explores potential challenges in the implementation of AI and DT technologies and subsequently offers insights into future trends.

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“…As a bridge connecting the physical real world and digital virtual space (Grieves, 2005;Tuegel et al, 2011), the digital twin technology enhances the self-perception, decision-making, and evolution capabilities of a power grid through modeling, simulation, and manipulation in virtual space, which can effectively support the data-driven digital twin research and various digital operations (Snijders et al, 2020;Zhang et al, 2020). The real-time calculation and analysis capabilities of digital twins can strengthen our understanding of the current and planned states of the power grid and improve the decision-making of operation and planning (Nguyen et al, 2021). It can be said that the construction of the power digital twin is an effective way to realize digital power grid and promote the construction of smart power grid (He et al, 2020;Wang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Ontology modeling method applied in simulation modeling of distribution network time series operation

et al. 2022

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Aiming at the difficulties in the realization of timing simulation in the digital twin environment, this article proposes an ontology modeling method applied to the simulation modeling of distribution network timing series operation. First, the two-layer ontology modeling architecture is introduced, and the power system domain structure ontology and the business-based application ontology are constructed. Second, based on the dynamic ontology modeling method, combined with the operational simulation business requirements, the sequential operation simulation ontology model is dynamically constructed. Finally, the effects of the modeling method in terms of simulation expression and modeling efficiency are shown through practical application example, and the modeling methods are compared and analyzed. The results provide a reference for the technical realization of power grid modeling in digital twin environments.

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Survey Paper of Digital Twins and their Integration into Electric Power Systems

Cited by 14 publications

References 20 publications

Sustainable Intelligent Transportation Systems via Digital Twins: A Contextualized Survey

Sustainable Intelligent Transportation Systems via Digital Twins: A Contextualized Survey

Emerging Information Technologies for the Energy Management of Onboard Microgrids in Transportation Applications

Ontology modeling method applied in simulation modeling of distribution network time series operation

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