Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System

Abstract

Motivated by the effects of deregulation over power quality and the subsequent need of new types of measurements, this paper assesses different implementations of an estimate for the spectral kurtosis, considered as a low-level harmonic detection. Performance of a processor-based system is compared with a field programmable gate array (FPGA)-based solution, in order to evaluate the accuracy of this processing function for implementation in autonomous measurement equipment. The fourth-order spectrum, with applications in different fields, needs advanced digital signal processing, making it necessary to compare implementation alternatives. In order to obtain reproducible results, the implementations have been developed using common design and programming tools. Several characteristics of the implementations are compared, showing that the increasing complexity and reduced cost of the current FPGA models make the implementation of complex mathematical functions feasible. We show that FPGAs improve the processing capability of the best processor using an operating frequency 33 times lower. This fact strongly supports its implementation in hand-held instruments.

Keywords

• reconfigurable computing
• FPGA
• power quality
• spectral kurtosis
• digital signal processing
• embedded system