Efficient data acquisition in advanced metering infrastructure

This paper will present a general and efficient methodology for data acquisition in Advanced Metering Infrastructure (AMI). Compressed distributed sensing using random walk (CDS(RW)) will be explored to acquire user load data from smart meters. This paper proposes to perform joint reconstruction of 2D user load profile using both spatial and temporal correlations. In this way, high data compression ratio can be achieved. Meanwhile, convex optimization will be the solver for the 2D user load profile reconstruction problem, which can guarantee both convergence and global optimality. Finally, taking power theft classification as a motivated example, this paper will demonstrate the performance will be acceptable even using the reconstructed user load profile for classification.