Digital Twin Adaptive Remedial Action Scheme for Preventing Voltage Collapse
This article introduces a real-time digital twin adaptive remedial action scheme (RAS) for the prevention of voltage collapse and the enhancement of stability and voltage performance. The scheme calculates the optimal load shedding amount in two stages, providing an effective solution to potential stability and voltage issues prior to implementation in the real power system. Unlike traditional approaches, which rely on offline studies and are labor intensive, the proposed scheme integrates a digital twin of the power grid to online tracing the power–voltage characteristic curves for real-time adjustments. The virtual model enables the real-time monitoring of voltage stability margin, facilitating virtual actions in the digital twin (DT) to adjust the load shedding amounts if necessary to reach safety conditions. A weighted least squares-based state estimator serves as a backup against measurement loss between the real power system and the DT. In addition, to ensure the desired voltage recovery, the RAS is based on the fault-induced voltage recovery criteria to recalculate load shedding amounts dynamically, based on voltage deviations, thus enabling the swift restoration of safe voltages and addressing transient behavior issues. The effectiveness of this RAS is demonstrated through its application to the IEEE 39 bus New England power system. Rigorous hardware-in-the-loop tests confirm its viability, showing significant performance enhancement.
Authors
- M. Á. Toro (ORCID: https://orcid.org/0000-0001-7460-2483)
- E. Barocio (ORCID: https://orcid.org/0000-0003-2311-7765)
- Aaron Esparza
- C. Nunez (ORCID: https://orcid.org/0000-0003-2451-421X)
- Nancy Visairo-Cruz (ORCID: https://orcid.org/0000-0003-1290-0586)
- Juan Segundo‐Ramírez (ORCID: https://orcid.org/0000-0001-6950-4133)
- Ulises Torres
Institutions
- Universidad de Guadalajara (MX)
- Autonomous University of San Luis Potosí (MX)
Publication Details
- Journal
- IEEE Journal of Emerging and Selected Topics in Industrial Electronics
- Published
- 2024-09-20
- DOI
- https://doi.org/10.1109/jestie.2024.3465429
- Citations
- 8
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 2.79