Isoperimetric clustering-based network partitioning algorithm for voltage–apparent power coupled areas

TLDR: An isoperimetric clustering based algorithm for partitioning power systems into voltage–apparent power coupled areas is proposed and it is shown that large networks can be represented as a weighted graph with number of vertices equal to number of generators in the system which is much lesser than the size of system, thereby reducing the computational effort for partitions.

Abstract: This work proposes a novel relative electrical distance measure that provides information of coupling between voltage and apparent power between two buses in power systems. Relative electrical distance measure is derived from the bus admittance matrix which can be obtained in real time using Phasor Measurement Units. Based on the relative electrical distance measure, in this work, an isoperimetric clustering based algorithm for partitioning power systems into voltage–apparent power coupled areas is proposed. The advantage of the partitioning algorithm proposed in this work is that large networks can be represented as a weighted graph with number of vertices equal to number of generators in the system which is much lesser than the size of system, thereby reducing the computational effort for partitioning. Isoperimetric clustering technique along with k-means is then applied to the graph to obtain voltage–apparent power coupled areas. Simulations carried out on New England 39-bus system and IEEE 118-bus system demonstrate the effectiveness of the proposed methodology for partitioning the system into voltage–apparent power coupled areas, subject to changes in the operating condition of the system. The quality of clustering is analysed and compared with Cheeger inequality bounds, which ensures that power system is well partitioned.