A Novel Method of Fuzzy Clustering for Substation Classification Based on Monte Carlo T-statistic Inspection
Lei Qingsheng · Dianli xitong zidonghua · 2011
Load classification is of great importance in load modeling.It is well known that it's difficult to judge the rationality of the type of a load substation through real time data and to check the validity and accuracy of the clustering results for lack of a checking method.The daily load data from EMS/SCADA is employed and its relative parameters are chosen as eigenvectors to classify the substation.A hypothesis proof-test based on formula T and Monte Carlo method are presented to guide the fuzzy clustering process and inspect the correctness of the clustering results.A case study shows the validity of the novel method through its application in a local power system.