The voltage sag area is the area of the power system that makes the voltage sag sensitive user unable to work properly. The concept of a voltage sag area is very useful for the evaluation of voltage sag severity. This paper shows that the existing sag area identification method requires many sample points, large calculation amount, and low recognition accuracy. Since those traditional method can cause fault in the identification of sag area, the process of calculating need to be improved. A systematic method that can identify sag area accurately is, therefore, proposed in this paper to address the need. The method is based on BP neural network, which uses the nonlinear fitting characteristics of BP neural network, is able to calculate the critical points of sag area accurately with limited fault points in large scale power system. Simulation studies in IEEE 30-bus test system shows that the proposed method can determine sag area correctly and to overcome limitations of other well-known methods.