Towards Highly Efficient State Estimation with Nonlinear Measurements in Distribution Systems

Abstract

This letter proposes a novel and highly efficient distribution system state estimation (DSSE) algorithm with nonlinear measurements from supervisory control and data acquisition (SCADA) systems. Conventional DSSE, i.e., a weighted least square (WLS)-based method, requires multiple Monte Carlo simulations for overall accuracy evaluation and has high calculation cost due to the nonlinear iterative process. The proposed method uses the Taylor series of voltages for constructing a linear DSSE model in the interval form and then solve this model by interval arithmetic. Compared with the nonlinear WLS-based method, the proposed method obtains accurate and robust estimates via a single random sampling of measurements and is computationally efficient. The comparative analysis of the IEEE 34-bus distribution system points to improved estimation results relative to the WLS-based method.