Using Of Sparse Principal Component Analysis For Identifying Critical Locations Of The Active Distribution System

This paper presents a method for the identification of critical locations of power systems using the measurable variables of the active distribution grids. The critical locations are identified using sensitive sparse principal component analysis (SSPCA) where the loadings of some variable in principal components are restricted to zero. SSPCA is tested on the UK 77-bus system. Furthermore, SSPCA and principal component analysis were investigated and the results analyzed and compared. The two methods provided comparable results in identification of critical locations. The validity and potential of SSPCA are demonstrated through simulation and a comparative study. The identification of critical locations in a power system will enable power operators/engineers using limited resources for prioritization of these locations for Phasor Measurement Units (PMUs) and other advanced measurement systems deployment.