Detection of Power Quality Disturbance Using a Multidimensional Approach in an Embedded System

Power Quality (PQ) has emerged as an important research field in recent years. The development and increasing use of high power converters and the increase of nonlinear loads with high power cause unwanted changes in the electrical signals (current and voltage). These changes are called electrical disturbances. To understand such disturbances and investigate their causes, they must be firstly detected. This work proposes a real time multidimensional approach for detecting PQ disturbances. The innovation of this work is the use of a deviation measure easily extracted from a multidimensional data space to quantify the PQ disturbances. The method was implemented in a FPGA (Field-programmable gate array) device using a LabVIEW interface. It performed well with high detection rates and low computational complexity for both simulated and real signals. The proposed deviation measure may be useful as a general power quality index.