Amplitude deviation (AD), frequency deviation (FD) and phase deviation (PD) are the important compositions of power quality disturbance (PQD). To analyze PQD deeply, this paper introduces a wavelet-based method for separating slight AD, FD and PD from a combined PQD, then quantifying and identifying them. The method is based on the fact that a linear-phase complex wavelet is certainly with an even real part and an odd imaginary part, or inversely. The distinctive characteristics of the method are: complex biorthogonal wavelet with the shortest smoothing filter (Haar filter), shift-invariant wavelet transform (WT) at a few scales, simple relationships between the WT coefficients and the magnitudes of AD, FD and PD, simple binary feature victor and binary-decimal conversion identifying process. These make the method simple, correct and fast.