Unsupervised clustering method and device for power system operating conditions

The invention provides an unsupervised clustering method and device for power system operating conditions, wherein the method comprises the following steps: obtaining power system power flow cross sections to be analyzed at different times, and constructing power flow vectors corresponding to each power flow cross section, wherein all power flow vectors constitute power flow vector spaces; using at-distribution random nearest neighbor embedding algorithm for data dimensionality reduction in the power flow vector space; using a hierarchical clustering algorithm for clustering analysis of the reduced dimension power flow vector space to obtain the clustering result of the operation conditions of the power system to be analyzed. In the clustering analysis of power system operating conditions, in addition to considering trend information, power network topology information is also used, the t-distribution stochastic nearest neighbor embedding algorithm is utilized to reduce the dimensionof power flow vector can e