Power quality disturbance detection and identification is the prerequisite and basis for the power quality management and control. This paper presents a new power quality disturbance detection and classification method. Firstly, the time-time transform is applied to power quality disturbance signal analysis. According to spectrum analysis results of the diagonal elements of time-time transform matrix, a preliminary judge about whether the disturbance signal contains harmonics and inter harmonic was given. For disturbances with non-harmonics, based on time-time transform modulus matrix diagonal sequence, the beginning and ending time of the disturbance is located, and the disturbance amplitude is calculated. For the disturbances which contain harmonics, time-time transform is perform twice to get the row mean value curve and the column mean value curve, which are required by disturbance time location and amplitude measurement. Finally, disturbance classification had realized by using rule tree. Simulation results reveal that this method is very robust and adaptable, which can identify transient power quality disturbance with minor magnitude under noisy environment, and the recognition rate is satisfactory.
Transient power quality disturbance denoising and detection based on improved iterative adaptive kernel regression
