Automatic Segmentation of Large Power Systems Into Fuzzy Coherent Areas for Dynamic Vulnerability Assessment

Abstract

This paper proposes a technique for partitioning a large power system into a number of coherent electric areas for possible application to dynamic vulnerability assessment. The coherency concept and a fuzzy clustering algorithm grouping of buses are combined to achieve this goal. The clusters are obtained by selecting representative buses from the data set in such a way that the total fuzzy dissimilarity within each cluster is minimized. The initialization problem of the conventional fuzzy c-means algorithm, which usually leads to multiple solutions, is suitably tackled by incorporating the maximum-dissimilarity based sequential phasor measurement unit (PMU) placement technique. Results of bus grouping for two test systems of three and nine areas demonstrate the potential of the approach. It is observed that such an approach to bus grouping results in a PMU configuration with minimum number of devices and fast data aggregation for a wide-area measurement system.