Sparse Estimation of Faults by Compressed Sensing With Structural Constraints

This paper addresses the challenge of fault location in large power networks using a limited number of sensors. It was recently shown that power system faults may be modeled by sparse vectors, and hence, can be located efficiently using sparse recovery techniques. In this paper, we extend this approach and propose a sparse recovery algorithm that exploits both the sparsity constraints and addition...