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A Power-Balanced Clustering Algorithm to Improve Electrical Infrastructure Resiliency

Timely evaluation of power system resiliency is important for power system operators and planners when they are confronting extreme weather or other large-scale natural disasters such as earthquakes or tsunamis. Intentional islanding operation is a solution to mitigate those threats because a proper islanding scheme has the potential to stop the propagation of cascading outages. Adequate partitioning of a large power grid is paramount in positioning different areas of the grid at good starting points for survival and reconnection. This paper builds upon a multi-objective electrical distance based clustering algorithm with i) a new index that ensures adequate amount of generation capacity for each cluster, ii) a new electrical distance matrix based on Q-V sensitivity, and iii) a simplification of the clustering method that shortens simulation times by equivalencing a given power system model. The results suggest that the new index improves upon the solutions that existing methods provide by enforcing the balance of load demand and power capacity within each cluster, while reducing computation time. These solutions are also consistent across the two electrical distance matrices that we consider in this work.

Author(s):

Chen Huo    
Oregon State University
United States

Eduardo Cotilla-Sanchez    
Oregon State University
United States

 

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