摘要：Fast and effective fault location in distribution system is important to improve the power system
reliability. Most of the researches rarely mention about effective fault location consisting of
faulted phase, fault type, faulty section and fault distance identification. This work presents a
method using support vector machine to identify the faulted phase, fault type, faulty section and
distance at the same time. Support vector classification and regression analysis are performed
to locate fault. The method uses the voltage sag data during fault condition measured at the
primary substation. The faulted phase and the fault type are identified using three-dimensional
support vector classification. The possible faulty sections are identified by matching voltage sag
at fault condition to the voltage sag in database and the possible sections are ranked using
shortest distance principle. The fault distance for the possible faulty sections isthen identified
using support vector regression analysis. The performance of the proposed method was tested on
an unbalanced distribution system from SaskPower, Canada. The results show that the accuracy
of the proposed method is satisfactory.
