A Robust State Estimation Framework for Active Distribution Network with Distribution-Level PMUs

This paper presents a robust, efficient and numerically stable Active Distribution Network State Estimation (ADNSE) framework. The pseudo measurements, substation measurements, and phasor measurements are used in the measurement vector. The pseudo measurements obtained from load buses are modelled as Gaussian distribution and that of Distributed Generation (DG) nodes are modelled as Gaussian mixture model. The phasor measurements are obtained from optimally located Distribution-level Phasor Measurement Units (DPMUs). The number and location of DPMUs are optimized using a new objective function. A new set of topological constraints are also proposed for direct monitoring of DG nodes, zero injection nodes, sub-station node and tie lines in the ADN. The efficacy of proposed framework is presented on UK 16, IEEE 33 and 119 test system using Monte Carlo simulations and found as robust against measurement loss, measurement degradation, network topology change and stochastic nature of DG.