Fault-phase selection is not only an important link on corrective actions of high-voltage transmission lines protection

but also an important prerequisite for accurate fault location.The traditional fault phase selection method is only applicable to simple fault

low sensitivity

and easily affected by system operation mode

fault grounding resistance etc.On the basis of the analysis for fault component of each phase current

this paper gives a definition of fault component energy by the concept of signal energy and presents a new type of fault phase identification method based on fault component energy coefficient.This method directly uses the fault current to extract fault components and calculate the signal energy of fault component for 2 cycles after fault inception

and the ratio coefficient that fault component energy of each phase current accounts the total energy can be gotten.Then probabilistic neural network of fault phase selection may be established to select fault phase by fault phase identification feature vector.Simulation results show that the method which has high capability is not affected by the initial phase angle of fault

the fault position and transition resistance.It can determine fault phases accurately.The theoretical analysis and simulation results verify the validity of the method.