A Methodology for Investigating Power Transmission Field-Observed Events Based on Digital Twins Combining Physical and Recorded Data

This paper presents a methodology for investigating power system occurrences based on constructing digital twins of the equipments and of the field-recorded events. The digital twins combine the data of the physical apparatus and the recorded measurements to reproduce the field conditions accurately. This methodology is a new approach in digital twin. It allows for a detailed analysis of situations that couldn't be fully understood with just physical or just measured data alone. The presented framework supports practitioners in uncovering the causes of events and settling informed engineering decisions in various scenarios, such as imbalances or unexpected overvoltages. A case study demonstrating how this approach was used to identify the cause of unexpectedly high neutral currents in transformers of an existing substation is presented. These high currents, caused by mechanical locks on the tap changer of one phase, led to unprogrammed tripping by the protection and interruptions in the full transmission service. By applying this methodology, the field conditions were accurately recreated, the analysis indicated the problem's cause, and the results supported the transmission utility in deciding to build connections to the tertiary windings to limit neutral currents in tap mismatch scenarios, highlighting the effectiveness and potential of this methodology.

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Publication Details

Journal
IEEE Transactions on Industry Applications
Published
2024-09-17
DOI
https://doi.org/10.1109/tia.2024.3462659
Primary Topic
Smart Grid and Power Systems
Type
article
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article

A Methodology for Investigating Power Transmission Field-Observed Events Based on Digital Twins Combining Physical and Recorded Data

Giovanni Manassero, Rodrigo Rozenblit Tiferes, Thiago Rodrigues Kleina Lima
IEEE Transactions on Industry Applications
Smart Grid and Power Systems
article

A Methodology for Investigating Power Transmission Field-Observed Events Based on Digital Twins Combining Physical and Recorded Data

Giovanni Manassero, Rodrigo Rozenblit Tiferes, Thiago Rodrigues Kleina Lima
article en

Abstract

This paper presents a methodology for investigating power system occurrences based on constructing digital twins of the equipments and of the field-recorded events. The digital twins combine the data of the physical apparatus and the recorded measurements to reproduce the field conditions accurately. This methodology is a new approach in digital twin. It allows for a detailed analysis of situations that couldn't be fully understood with just physical or just measured data alone. The presented framework supports practitioners in uncovering the causes of events and settling informed engineering decisions in various scenarios, such as imbalances or unexpected overvoltages. A case study demonstrating how this approach was used to identify the cause of unexpectedly high neutral currents in transformers of an existing substation is presented. These high currents, caused by mechanical locks on the tap changer of one phase, led to unprogrammed tripping by the protection and interruptions in the full transmission service. By applying this methodology, the field conditions were accurately recreated, the analysis indicated the problem's cause, and the results supported the transmission utility in deciding to build connections to the tertiary windings to limit neutral currents in tap mismatch scenarios, highlighting the effectiveness and potential of this methodology.

IEEE Transactions on Industry ApplicationsVol. 61(2)
Institute of Power Engineering (PL), Departamento de Ciência e Tecnologia (BR)
Affordable and clean energy
Openalex Percentile: Top 87%
Smart Grid and Power Systems
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A Methodology for Investigating Power Transmission Field-Observed Events Based on Digital Twins Combining Physical and Recorded Data — Giovanni Manassero, Rodrigo Rozenblit Tiferes, et al. · IEEE Transactions on Industry Applications (2024) | TGRS Research Map | TGRS