Learning Platform for Power Quality Surveillance

Abstract

In recent years, power quality (PQ) has become a major concern due to the increasing complexity of modern power systems within the integration of distributed energy resources. This paper presents the design and implementation of a learning platform for their PQ surveillance. The proposed design consists of two independent but also complementary modules. With time-compression capabilities, the first one is a signal processing module; it is based on higher-order statistics (HOS) and it is thought to monitor and characterize the voltage; its counterpart is oriented to statistical learning, and it detects and classifies PQ events. The aim of this platform is to enable both undergraduate and graduate engineering students to analyze modelling techniques for event analysis via different lessons with the underlying goal of approaching to real-life practice.