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.
Authors
- Giovanni Manassero (ORCID: https://orcid.org/0000-0003-1280-1422)
- Rodrigo Rozenblit Tiferes (ORCID: https://orcid.org/0000-0003-1153-7455)
- Thiago Rodrigues Kleina Lima (ORCID: https://orcid.org/0009-0004-8685-621X)
Institutions
- Institute of Power Engineering (PL)
- Departamento de Ciência e Tecnologia (BR)
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
- Field-Weighted Citation Impact
- 0.00