Classification and Identification of Power Quality Disturbances Based on Stochastic Forest Model
With the emergence and use of a large number of new power electronic equipment, the power supply department has begun to pay extensive attention to the problem of power quality, and the majority of users have put forward higher requirements for the quality of power supply. This paper studies the classification and identification method of power quality disturbances based on random forest model. In this paper, according to IEEE power quality standard, the normal waveform and 16 common power quality disturbance waveforms are mathematically modeled, and the power quality disturbance signal is analyzed by S-transform. In this paper, the power quality disturbance identification algorithm based on random forest is optimized. Experimental data show that the optimized method has higher disturbance recognition accuracy and better anti noise ability. Therefore, using the power quality disturbance identification method proposed in this paper to monitor the power quality of power grid is of great significance to ensure the safe and stable operation of power grid and improve economic benefits.