Research On Fault Location In Distribution Network With DG Based On Differential Evolution Algorithm And Fault Feature

The precise fault location is a problem that has not been well solved. The applition ofdistribution generation (DG) increases the difficulty of fault location. And its research playsan important role in restoring power supply and reducing the economic loss.The fault location in distribution network with DG has been a hot and difficulty researchat home and abroad. Although many fault location methods have been improved consideringthe features of the distribution network with DG, most of the methods have some limitations.A new fault location method in distribution network with DG is proposed based on theimpendence methods and the fault characteristics matching method in this paper. Theimpendence model and the fault characteristics matching of the differential evolutionalgorithm are both applied in this new method. First the three-phase impendence models andthe zero sequence impedance models are built. The fault characteristics in the impendencemodel of the distribution network with DG are analyzed and extracted. Then the fault sectionlocation technology is realized by using the impendence model and the fault characteristics.The differential evolution algorithm is used to precisely located fault in distribution networkwith DG based on the impendence model of the system and the fault section. The variables ofthe differential evolution algorithm are the fault distance and the grounded resistance. Thefitness function of the differential evolution algorithm is the value of the fault characteristic.The differential evolution algorithm can quickly search the optimal fault conditions. Theprecise location of the fault is found. The simulation results show that the impendence modelof the system, the fault section location method and the fault location method are all effective.The approach proposed in this paper overcomes the disadvantages that the accuracy ofthe existing impendence method is low and the speed of the existing feature matching methodis slow. It applies to the complex distribution network with DGs. This method has importanttheoretical and practical value.