Applications of Digital Twins in Power Systems: A Perspective
| aut.relation.journal | Transactions on Energy Systems and Engineering Applications | en_NZ |
| dark.contributor.author | Kamyabi, L | en_NZ |
| dark.contributor.author | Lie, TT | en_NZ |
| dark.contributor.author | Madanian, S | en_NZ |
| dc.contributor.author | Kamyabi, Leila | |
| dc.contributor.author | Lie, Tek Tjing | |
| dc.contributor.author | Madanian, Samaneh | |
| dc.date.accessioned | 2025-01-29T21:37:10Z | |
| dc.date.available | 2025-01-29T21:37:10Z | |
| dc.date.copyright | 2022-11-04 | en_NZ |
| dc.date.issued | 2022-11-04 | en_NZ |
| dc.description.abstract | Data science-based digital twin models of renewable energy system technologies developed in a real-time data-rich environment help develop better decisions and predictions than those in the present environment. Based on this real-time analysis of countrywide data, digital twin contributes to effective and reduced cost-based power system control at the localised level. Developing digital twin models from the collection of relevant data is an innovative technology. The challenge is how to leverage all the operational data and analyse the use of data from across transmission and distribution networks to help achieve the objectives. This paper presents an overview of the existing applications of digital twins in power systems. | |
| dc.identifier.citation | Kamyabi, L., Lie, T. T., & Madanian, S. (2022). Applications of Digital Twins in Power Systems: A Perspective. Transactions on Energy Systems and Engineering Applications, 3(2), 1–9. https://doi.org/10.32397/tesea.vol3.n2.484 | |
| dc.identifier.doi | 10.32397/tesea.vol3.n2.484 | en_NZ |
| dc.identifier.issn | 2745-0120 | en_NZ |
| dc.identifier.uri | http://hdl.handle.net/10292/18507 | |
| dc.publisher | Universidad Tecnológica de Bolívar | |
| dc.relation.uri | https://revistas.utb.edu.co/tesea/article/view/484 | |
| dc.rights | Copyright (c) 2022 Tek Tjing Lie, Leila Kamyabi, Samaneh Madanian. This work is licensed under a Creative Commons Attribution 4.0 International License. | |
| dc.rights.accessrights | OpenAccess | en_NZ |
| dc.rights.license | Creative Commons Attribution 4.0 International License. | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.title | Applications of Digital Twins in Power Systems: A Perspective | en_NZ |
| dc.type | Journal Article | |
| pubs.elements-id | 482546 | |
| pubs.organisational-data | /AUT | |
| pubs.organisational-data | /AUT/Faculty of Design & Creative Technologies | |
| pubs.organisational-data | /AUT/Faculty of Design & Creative Technologies/School of Engineering, Computer & Mathematical Sciences |
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