Power Quality Disturbances Detection using Multi-Resolution Analysis Technique

Power quality (PQ) is a critical concern for individuals and organizations that rely on equipment and systems. There are numerous types of PQ events that users may encounter, making it essential to have a thorough understanding of the causes and effects of these events. To analyze these events and determine their parameters, it is necessary to study the topic and conduct an analysis. One technique used in this process is multi-resolution analysis (MRA), which allows a waveform to be represented by its different frequency bands using an algorithm. Characteristics such as orthogonality and symmetry can help to reconstruct the signal with minimal error and are useful for compressed audio and video applications. PQ events can generally be classified into several categories, including voltage transients, frequency variations, and power factor disturbances. This paper focuses on the simulation, detection, and localization of Power Quality (PQ) events using advanced tools such as wavelet transform. The signals are first de-noised by applying wavelet transform, which allows the detection of the starting and ending points of the eruption in the time domain. This decomposes the signal into multiple levels, enabling the detection and localization of the time and frequency of the eruption. In addition, an analysis of the types of PQ events is performed.