A Robust Method for Distribution System State Estimation with Predator-Prey Brain Storm Optimization

Abstract

In this paper, a new method is proposed for distribution system static state estimation with low redundant measurements. It is different from transmission system static state estimation because the distribution system static state estimation has low redundancy of measurements while the transmission system static state estimation has enough redundancy. This paper makes use of the nest structure of DistFlow of the distribution system power flow calculation to transform the formulation into evaluating the state variable vector at distribution substations. In other words, the distribution state estimation problem may be expressed as an optimization problem. As the optimization method, PPBSO (Predator-Prey Brain Storm Optimization) of evolutionary computation is proposed to solve the problem. The proposed method is successfully applied to a sample system.