Abstract
In recent years, power systems are more complicated and prone to instability due to the presence of renewable energy resources. Therefore, the controlled power system islanding is proposed as the last resort to prevent system instability. The aim of controlled islanding is to create stable islands in the grid, in order to prevent global blackout and facilitate total system restoration. Therefore, a proper decision-making algorithm is required to determine the separation points in a very short time. In this paper, a novel hierarchical spectral clustering method is introduced, which meets the practical requirements and constraints of power system islanding. Moreover, this approach leads to several clustering candidate solutions simultaneously, which can be optimally selected based on a desired objective function. The proposed approach is evaluated on IEEE test systems and compared to the existing methods. The simulation results show that the proposed method is computationally more efficient than other existing approaches.
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