Study On The Methods Of Detection And Location Of Voltage Sag

With the rapid development of modern power electronics technology and computer technology, more and more sensitive electrical equipment put forward higher requirements for power quality. At present, the equipment fault electricity complaints caused by voltage sag problems surge sharply. So, the problem of voltage sag causes the experts’ attention and become one of the most important power quality problems. In the research of sag problems, whether can rapidly and accurately detect the characteristics like begin-end time and amplitude of voltage sag, it will determine the subsequent sag compensation and governance effect. For voltage sag disturbance source location, only after information about a disturbance location is available, can diagnosis and mitigation strategy be carried out. Moreover, any disputes can be resolved fairly.This thesis introduces the voltage sag detection algorithm and the location methods of disturbance source. First of all, it introduces several traditional detection algorithms and analyzes their advantages and disadvantages through simulation. Aiming at the defects of the traditional algorithm can’t detect in real time, this thesis adopts the HHT algorithm based on EEMD. It realizes accurate detection by achieving the begin-end time and the amplitude changes of sag through the instantaneous frequency and instantaneous amplitude, the simulation result turns out to be fast and accurate.Then introduces some types of the common disturbance source location method, and verifies their positioning accuracy by simulation. Aiming at the shortcomings of the traditional positioning methods’ low accuracy, this thesis uses an intelligent location method based on support vector machine. According to location characteristic in the process of voltage sag, we can apply the thought of two classification of support vector machine to establish a multi-dimensional vector space, through looking for the classified the optimal hyperplane to realize sag source location. The testing results show that method could locate the voltage sag source effectively with a minimum of time.