Cargando…

Off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis

Currently, the methods used to represent loads do not differ between the characteristics that compose them or the nature of these. Therefore, the purpose of this research is to develop digital twins mirroring load models that can be used for more precise studies on power-flows and stability within t...

Descripción completa

Detalles Bibliográficos
Autores principales: Urquizo, Javier, Ramirez, Nathalie, Sanchez, Dietmar, Plazarte, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10030858/
https://www.ncbi.nlm.nih.gov/pubmed/36944720
http://dx.doi.org/10.1038/s41598-023-31451-9
_version_ 1784910470167134208
author Urquizo, Javier
Ramirez, Nathalie
Sanchez, Dietmar
Plazarte, Juan
author_facet Urquizo, Javier
Ramirez, Nathalie
Sanchez, Dietmar
Plazarte, Juan
author_sort Urquizo, Javier
collection PubMed
description Currently, the methods used to represent loads do not differ between the characteristics that compose them or the nature of these. Therefore, the purpose of this research is to develop digital twins mirroring load models that can be used for more precise studies on power-flows and stability within the National Transmission Grid (NTG). Off-line sampling data of different electric measurements have been used in six substations of the Guayaquil (Ecuador) area. These values were organized by statistical methods and by time periods, to determine the parameters that make up the static load model. Dynamic models are also constructed for the same six substations using the analysis of current and voltage signals obtained from the substations. All data is organized to show a digital twin mirroring visual representation of the disturbances that may occur in the substation buses. A more accurate description of the static and dynamic responses can be obtained by replacing the general model that is currently used by engineers and planners with off-line sampling data. Digital twins help the electric utility businesses gather, visualise, and contextualise data from different sources, and enable to act on data, and to understand what-if modelling stability scenarios.
format Online
Article
Text
id pubmed-10030858
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-100308582023-03-23 Off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis Urquizo, Javier Ramirez, Nathalie Sanchez, Dietmar Plazarte, Juan Sci Rep Article Currently, the methods used to represent loads do not differ between the characteristics that compose them or the nature of these. Therefore, the purpose of this research is to develop digital twins mirroring load models that can be used for more precise studies on power-flows and stability within the National Transmission Grid (NTG). Off-line sampling data of different electric measurements have been used in six substations of the Guayaquil (Ecuador) area. These values were organized by statistical methods and by time periods, to determine the parameters that make up the static load model. Dynamic models are also constructed for the same six substations using the analysis of current and voltage signals obtained from the substations. All data is organized to show a digital twin mirroring visual representation of the disturbances that may occur in the substation buses. A more accurate description of the static and dynamic responses can be obtained by replacing the general model that is currently used by engineers and planners with off-line sampling data. Digital twins help the electric utility businesses gather, visualise, and contextualise data from different sources, and enable to act on data, and to understand what-if modelling stability scenarios. Nature Publishing Group UK 2023-03-21 /pmc/articles/PMC10030858/ /pubmed/36944720 http://dx.doi.org/10.1038/s41598-023-31451-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Urquizo, Javier
Ramirez, Nathalie
Sanchez, Dietmar
Plazarte, Juan
Off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis
title Off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis
title_full Off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis
title_fullStr Off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis
title_full_unstemmed Off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis
title_short Off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis
title_sort off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10030858/
https://www.ncbi.nlm.nih.gov/pubmed/36944720
http://dx.doi.org/10.1038/s41598-023-31451-9
work_keys_str_mv AT urquizojavier offlinemeasuringsamplingdataidentificationparametersfordigitaltwinsmirroringloadmodellingandstabilityanalysis
AT ramireznathalie offlinemeasuringsamplingdataidentificationparametersfordigitaltwinsmirroringloadmodellingandstabilityanalysis
AT sanchezdietmar offlinemeasuringsamplingdataidentificationparametersfordigitaltwinsmirroringloadmodellingandstabilityanalysis
AT plazartejuan offlinemeasuringsamplingdataidentificationparametersfordigitaltwinsmirroringloadmodellingandstabilityanalysis