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Abstract-Controlled islanding is an active and effective way of avoiding catastrophic wide area blackouts. It is usually considered as a constrained combinatorial optimization problem. However, the combinatorial explosion of the solution space that occurs for large power systems increases the complexity of solving it. This paper proposes a two-step controlled islanding algorithm that uses spectral clustering to find a suitable islanding solution for preventing the initiation of wide area blackouts by un-damped electromechanical oscillations. The objective function used in this controlled islanding algorithm is the minimal power-flow disruption. The sole constraint applied to this solution is related to generator coherency. In the first step of the algorithm, the generator nodes are grouped using normalized spectral clustering, based on their dynamic models, to produce groups of coherent generators. In the second step of the algorithm, the islanding solution that provides the minimum power-flow disruption while satisfying the constraint of coherent generator groups is determined by grouping all nodes using constrained spectral clustering. Simulation results, obtained using the IEEE 9-, 39-, and 118-bus test systems, show that the proposed algorithm is computationally efficient when solving the controlled islanding problem, particularly in the case of a large power system.

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefit of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unifie framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.

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Abstract:Intentional controlled islanding is an effective corrective approach to minimise the impact of cascading outages leading to large-area blackouts. This paper 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 our methodology is more efficient, in a factor of approximately 10, and more accurate than another existing approach for minimal power flow disruption.