Automated analysis of power quality disturbances

This paper presents developments related to automated analysis of power quality (PQ) disturbance. The proposed approaches consist of several steps that may be closely related to each other. The PQ disturbance is first detected and classified by an automated system. After the type of disturbance is identified, the distinctive features of the waveform are appropriate modules. Then, the equipment of interest can be studied under this specific disturbance. If this disturbance is identified as a sag caused by a fault. the genetic algorithm based search approach is utilized to locate the fault. Examples are presented to illustrate the applications of the developed methodology and tools. It is found that appropriate interaction between data analysis and system modeling is an efficient way for carrying out PQ studies. Both recorded and simulated data have been evinced to be useful for PQ analysis.