Performance Comparison of Advanced Techniques for Voltage Dip Detection

Different aspects have to be considered when dealing with voltage dips in electric power systems. As a consequence, according to different needs arising from specific applications, different approaches have been proposed in the literature for the detection and classification of these events. This paper focuses on issues that are critical for the development of real-time compensation systems, namely, the capability of detecting correctly and rapidly the event while avoiding false alarms, and the algorithm complexity. To this purpose, approaches based on voltage root mean square, wavelets, Kalman filtering, peak voltage, missing voltage, and generalized likelihood ratio test are compared by means of computer simulations, by considering different kinds of voltage dips and by taking into account the uncertainty introduced by noise. The results provide meaningful indication on the choice of the most suitable method to be used in the considered applications.