State Estimation of Asymmetrical Distribution Networks by μ-PMU Allocation: A Novel Stochastic Two-stage Programming

Abstract

• The WLS-based state estimation algorithm developed in this research can simulate large-scale asymmetric distribution networks. • An effective DSSE model is implemented based on a limited number of μ-PMUs and ZINs for determining the state variables. • Using the ZIN characteristics to minimize the μ-PMUs number in the system and keep the system fully observable. • The linear approximations are applied to model the linear DSSE. Distribution system state estimation provides essential data for the system monitoring and control, which some uncertain parameters such as the intermittent and varying output of distributed generation (DG), random meter errors, and inaccurate network parameters make situational awareness (SA) of distribution systems a challenging issue. To address these issues, this paper develops an innovative two-stage stochastic programming model, where in the first stage, optimal μ-PMU placement is implemented aiming at minimizing the installation cost of μ-PMU and maximizing the number of measurement redundancy and the system observability in the presence of partially zero injection nodes (PZIN), while in the second stage state estimation of three-phase asymmetric DG-integrated distribution systems is performed to enhance SA. By applying the proposed model, the optimal locations of μ-PMUs in the presence of PZINs and various contingencies were achieved, and the distribution system state estimation was obtained with high accuracy and low error percentage. The feasibility of the proposed methodology is verified on the modified IEEE 85-bus distribution system.