Constrained spectral clustering based methodology for intentional controlled islanding of large-scale power systems

Abstract

Intentional controlled islanding is an effective corrective approach to minimise the impact of cascading outages leading to large-area blackouts. This study proposes a novel methodology, based on `constrained spectral clustering', that is computationally very efficient and determines an islanding solution with minimal power flow disruption, while ensuring that each island contains only coherent generators. The proposed methodology also enables operators to constrain any branch, which must not be disconnected, to be excluded from the islanding solution. The methodology is tested using the dynamic models of the IEEE 39- and IEEE 118-bus test systems. Time-domain simulation results for different contingencies are used to demonstrate the effectiveness of the proposed methodology to minimise the impact of cascading outages leading to large-area blackouts. In addition, a realistically sized system (a reduced model of the Great Britain network with 815 buses) is used to evaluate the efficiency and accuracy of the methodology in large-scale networks. These simulations demonstrate that the author's methodology is more efficient, in a factor of approximately 10, and more accurate than another existing approach for minimal power flow disruption.

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Identifiers

ORCID for Ruben Sanchez-Garcia: orcid.org/0000-0001-6479-3028

ORCID for Jacek Brodzki: orcid.org/0000-0002-4524-1081

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