Comparative Performance Analysis of Optimization Based Distribution System State Estimator with Varying Measurement Uncertainties

Abstract

State estimator (SE) is the core of every distribution system analysis software. Quality of the state estimates depends on the quality of measurements available. Most distribution systems are sparsely monitored. Therefore, any information available is of utmost importance. A state estimator uses large number of pseudo and virtual measurements in addition to real measurements, for performing distribution system state estimation. Typical characteristics of a distribution system and also the inclusion of virtual measurement in state estimation causes convergence issues due to ill-conditioning of gain matrix. This paper aims at developing a detailed three-phase model of a distribution network and explores the application of state of the art convex optimization techniques for distribution system state estimation. A comparative study of these methods on accuracy and convergence of a distribution system state estimator is also presented.