Signal processing deployment in power quality disturbance detection and classification

Abstract

Power quality disturbances have adverse impacts on the electric power supply as well as on the customer equipment. Therefore, the detection and classification of such problems is necessary. In this paper, a fast detection algorithm for power quality disturbances is presented. The proposed method is a hybrid of two algorithms, abc–0dq transformation and 90 phase shift algorithms. The proposed algorithm is fast and reliable in detecting most voltage disturbances in power systems such as voltage sags, voltage swells, voltage unbalance, interrupts, harmonics, etc. The three-phase utility voltages are sensed separately by each of the algorithms. These algorithms are combined to explore their individual strengths for a better performance. When a disturbance occurs, both algorithms work together to recognize this distortion. This control method can be used for critical loads protection in case of utility voltage distortion. Simulation and analysis results obtained in this study illustrate high performance of the strategy in different single-phase and three-phase voltage distortions