Identification of Critical Generators in Transient Stability Problems
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Abstract
The literature has focused on transient stability, concentrating on its assessment and control under operational situations and limited contingencies. This often leads to transient stability issues not addressed in studies, making the system vulnerable to imminent collapses. In this context, this work proposes a methodology for identifying critical generators under a broad range of operational scenarios and contingencies, serving as a foundation for the development of an adaptable disconnection scheme that responds to the system's real-time dynamics. The methodology relies on the generation of a database encompassing a wide spectrum of operational scenarios and N-1 contingencies, as well as the systematic disconnection of generators to identify those deemed critical for mitigating transient instability. In a controlled simulation environment (IEEE New England 39-bus system in DigSILENT Power Factory software), the methodology effectively identified critical generators in 99.6% of the simulated cases deemed unstable due to transient stability issues, thereby establishing a solid foundation for training a learning model that operates in real time according to the system's dynamics, which translates into an adaptable generation disconnection scheme.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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La Revista Técnica "energía" está bajo licencia internacional Creative Commons Reconocimiento-NoComercial 4.0.
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