Digital Twins: From Conceptual Views to Industrial Applications in the Electrical Domain

Serugendo, Giovanna Di Marzo; Cutting-Decelle, Anne-Françoise; Guise, L.; Cormenier, T.; Khan, Imran

doi:10.1109/mc.2022.3156847

Cited by 9 publications

(6 citation statements)

References 13 publications

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“…The application of DT started in the field of aeronautics and has expanded to other areas, such as airframes [61,62], industry [63,64], product service systems [65,66], systems engineering [67], health care [68,69], structural health monitoring [70], product design [71], product life cycle management [72], construction [73], urban planning and transportation [74,75], disaster management [76], infrastructure management [77], agriculture [72,78], and more. While most use cases of DT are in the field of manufacturing [79], the development of DT in the construction industry was not achieved until 2018 [73,80].…”

Section: Digital Twin Definitionmentioning

confidence: 99%

Digital Twin for Fault Detection and Diagnosis of Building Operations: A Systematic Review

Hodavand,

Ramaji,

Sadeghi

2023

Buildings

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Intelligence in Industry 4.0 has led to the development of smart buildings with various control systems for data collection, efficient optimization, and fault detection and diagnosis (FDD). However, buildings, especially with regard to heating, ventilation, and air conditioning (HVAC) systems, are responsible for significant global energy consumption. Digital Twin (DT) technology offers a sustainable solution for facility management. This study comprehensively reviews DT performance evaluation in building life cycle and predictive maintenance. 200 relevant papers were selected using a systematic methodology from Scopus, Web of Science, and Google Scholar, and various FDD methods were reviewed to identify their advantages and limitations. In conclusion, data-driven methods are gaining popularity due to their ability to handle large amounts of data and improve accuracy, flexibility, and adaptability. Unsupervised and semi-supervised learning as data-driven methods are important for FDD in building operations, such as with HVAC systems, as they can handle unlabeled data and identify complex patterns and anomalies. Future studies should focus on developing interpretable models to understand how the models made their predictions. Hybrid methods that combine different approaches show promise as reliable methods for further research. Additionally, deep learning methods can analyze large and complex datasets, indicating a promising area for further investigation.

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Section: Digital Twin Definitionmentioning

confidence: 99%

Digital Twin for Fault Detection and Diagnosis of Building Operations: A Systematic Review

Hodavand,

Ramaji,

Sadeghi

2023

Buildings

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“…In fact, they are also "intelligent" digital twins, since they interact, make decisions based on the information collected, and have advanced capabilities such as negotiating or learning [21].…”

Section: Using Intelligent Digital Twinmentioning

confidence: 99%

“…Within the coordination model, digital twins go beyond real-time replicas, since they are equipped with advanced functionalities (e.g., sensing, acting, learning, negotiating, etc.) [21]. They are actual software agents working on behalf of actual devices or users.…”

Section: Intelligent Digital Twinsmentioning

confidence: 99%

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Coordination Model and Digital Twins for Managing Energy Consumption and Production in a Smart Grid

Glass,

Di Marzo Serugendo

2023

Energies

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Smart grids play an important role for energy management by directly supporting the socio-ecological transition of neighbourhoods. This research provides the design of a coordination model to enable the management and exchange of electrical energy between producers and consumers at a micro-grid level. This model, which derives from the SAPERE coordination model, allows the intelligent digital twins to interact and generate services on the fly to meet different needs in real time. We have designed producer and consumer digital twins, which autonomously generate supply contracts in the form of a transaction, and supervisor digital twins, which regulate energy at the node level, managing threshold violations and proactively avoiding future threshold violations by using predictions. This coordination model allows energy exchanges in a single node and in a micro-grid structure that contains several neighbouring nodes. We have implemented and tested the platform with realistic data, based on the consumption statistics of a real household, and with real data, collected in the living-lab of “Les Vergers” located near Geneva. The results show that the combination of a coordination model and intelligent digital twins actually supports self-adaptive energy management in a smart grid. Such approaches are fundamental to develop efficient and reliable smart grids.

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“…This again highlights the importance of our research in building social acceptance into the design from the outset. This is what we intend to do in future research by integrating these social acceptance requirements into the scenarios that will feed a digital twins approach [14] and thus develop coherent simulation scenarios (technical as well as social).…”

Section: Literature Reviewmentioning

confidence: 99%

Improving the Social Acceptability of Microgrids

Fragniere,

Sandoz,

Abdenadher

et al. 2023

2023 IEEE Renewable Energy and Sustainable E-Mobility Conference (RESEM)

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The smart grid will have to occupy a prominent place in people's lives in the years to come, as the renewable energy mix desired by all governments implies a change of role from consumer to prosumer (contraction of the consumer to producer) of electricity. The adoption of micro smart grid technology, which links solar panels, batteries, and inverters to smart meters and power regulation algorithms, by a community (e.g., a residential sector), cannot be done automatically. This is what we studied in Switzerland, based on a qualitative survey (12 semistructured interviews and 4 focus groups) to understand the psychological and social barriers, which prevent people from integrating such a technology. The results show that restraining forces are more important than driving forces and therefore that governments need to tackle the problem of social acceptance of smart grids before focusing on mainly technological aspects in their long-term energy and environmental policies.

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Digital Twins: From Conceptual Views to Industrial Applications in the Electrical Domain

Cited by 9 publications

References 13 publications

Digital Twin for Fault Detection and Diagnosis of Building Operations: A Systematic Review

Digital Twin for Fault Detection and Diagnosis of Building Operations: A Systematic Review

Coordination Model and Digital Twins for Managing Energy Consumption and Production in a Smart Grid

Improving the Social Acceptability of Microgrids

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