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

机译:基于约束谱的聚类分析方法,用于大规模电力系统的有意控制孤岛化

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摘要

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.
机译:故意控制的孤岛效应是一种有效的纠正方法,可以最大程度地减少级联中断导致大面积停电的影响。本文提出了一种基于约束频谱聚类的新颖方法,该方法在计算上非常有效,可确定具有最小潮流中断的孤岛解决方案,同时确保每个孤岛仅包含相干发生器。所提出的方法还使运营商能够约束必须断开的任何分支,以将其从孤岛解决方案中排除。使用IEEE 39总线和IEEE 118总线测试系统的动态模型对方法进行了测试。使用针对不同突发事件的时域仿真结果来证明所提出方法的有效性,该方法可最大程度地减少级联中断导致大面积停电的影响。另外,使用一个实际大小的系统(具有815总线的大不列颠网络的简化模型)来评估大规模网络中该方法的效率和准确性。这些仿真表明,与其他现有方法相比,我们的方法更有效,效率最高,约为10倍,并且更精确,可以最大程度地减少电流中断。

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