An Improved Reconstruction Algorithm Based on Compressed Sensing for Power Quality Analysis in Wireless Sensor Networks of Smart Grid

Abstract

In recent years, the growing power quality problems in smart grid cause widespread concern at home and abroad. Because the traditional power quality algorithms which are based on Nyquist sampling theory have the drawbacks of complicated, heavy computations and poor real-time performance when sampling and analyzing continuous massive signals in smart grid. This paper discussed an improved reconstruction algorithm based on compressed sensing due to the sparsity of power quality signals in frequency domain for power quality analysis .By using the ZigBee wireless gateway for wireless sensor networks and energy metering chip, we develop a single meter node to do relative experiments. In the condition of the real test-bed and several compared experiments, power quality information in the highly compression ratio has good performance according to CSR (Compression Sampling Ratio), SNR (Signal to Noise Ratio), MSE (Mean Squared Error) and ERP (Energy Recovery Percentage) , and will be widely used in power quality analysis.