An Optimal Set of Measurements for the Estimation of System States in Large-Scale Power Networks

Abstract

This paper addresses the problem of measurement selection and meter locations as related to the power system state estimation. The measurement redundancy is selected as a criterion, and based on the redundancy identification technique applied to linearly constrained mathematical programming problems, a method is proposed to identify redundant measurements among a given set of measurements. Such an identification will determine an adequate set of measurements for state estimators that adopt mathematical programming techniques. The method is rather simple, yet it significantly contributes towards the solution of the measurement selection problem and can be implemented off-line and on real-size systems.