Line outage detection using support Vector Machine (SVM) based on the Phasor Measurement Units (PMUs) technology

Phasor Measurement Units (PMUs) have been increasingly widespread throughout the power network. As a result, several researches have been made to locate the PMUs for complete system observability. Many protection applications are based upon the PMUs locations. This paper introduces an important application in power system protection which is the detection of single line outage. In addition, a detection of the outaged line is achieved depending on the variations of phase angles measured at the system buses where the PMUs are located. Hence, a protection scheme from unexpected overloading in the network that may lead to system collapse can be achieved. Such detections are based upon an artificial intelligence technique which is the support Vector Machine (SVM) classification tool. To demonstrate the effectiveness of the proposed approach, the algorithm is tested using offline simulation for the 14-bus IEEE system.