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Representative operating and contingency scenarios for the design of UFLS schemes

L. Sigrist, I. Egido, E.F. Sánchez-Úbeda, L. Rouco

IEEE Transactions on Power Systems Vol. 25, nº. 2, pp. 906 - 913

Resumen:

This paper studies an approach to identify representative operating and contingency (OC) scenarios for the design of underfrequency load-shedding (UFLS) schemes. In small isolated power systems, contingency scenarios are outages of generating units. Usually, only N-1 outages are considered. In this paper, simultaneous outages of several units are also taken into account. Data mining techniques such as K-Means and Fuzzy C-Means algorithms are used to group scenarios in terms of system frequency and to identify representative OC scenarios. The approach has been applied to the design of UFLS schemes of two of the Spanish isolated power systems. The results have also been compared to the common practice of scenario selection. Clustering techniques yielded to satisfactory results, i.e., representative OC scenarios can be identified. Furthermore, these representative OC scenarios cover a wider range of possible system responses than the scenarios selected following the common practice.


Palabras Clave: Clustering methods, frequency stability, load shedding


Índice de impacto JCR y cuartil WoS: 2,355 (2010); 6,600 - Q1 (2022)

Referencia DOI: DOI icon https://doi.org/10.1109/TPWRS.2009.2031839

Publicado en papel: Mayo 2010.

Publicado on-line: Noviembre 2009.



Cita:
L. Sigrist, I. Egido, E.F. Sánchez-Úbeda, L. Rouco, Representative operating and contingency scenarios for the design of UFLS schemes. IEEE Transactions on Power Systems. Vol. 25, nº. 2, pp. 906 - 913, Mayo 2010. [Online: Noviembre 2009]


    Líneas de investigación:
  • *Estabilidad: estabilidad de gran perturbación, ajuste de protecciones de deslastre de cargas por frecuencia, control de la excitación, estabilidad de pequeña perturbación, ajuste de estabilizadores del sistema de potencia, identificación de modelos de reguladores
  • *Predicción y Análisis de Datos

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