Flexible data acquisition, compression, and reconstruction in advanced metering infrastructure

Abstract

This paper will design a general, flexible, and efficient framework for data acquisition, data compression, and data reconstruction in advanced metering infrastructure (AMI). Compressed distributed sensing will be utilized to acquire load data from smart meters and transmit them to the central control unit. Different sparse binary measurement matrices will be exploited for different time instances when data acquisitions are performed. Each sparse binary measurement matrix corresponds to one data gathering scheme using compressed distributed sensing. This paper proposes to perform joint reconstruction of the two-dimensional load profile at the central control unit. Both spatial and temporal correlations will be explicitly employed to facilitate data reconstruction with high accuracy and fidelity. Meanwhile, the desirable data compression ratio can be achieved.