Towards Highly Efficient State Estimation With Nonlinear Measurements in Distribution Systems
Ying Zhang, Jianhui Wang
Abstract
This letter proposes a novel and highly efficient distribution system state estimation (DSSE) method with nonlinear measurements from supervisory control and data acquisition (SCADA) systems. Conventional DSSE based on the weighted least square (WLS) criterion requires multiple Monte Carlo simulations for overall accuracy evaluation and high calculation cost due to a nonlinear iterative process. The proposed method uses the Taylor series of voltages for constructing a linear DSSE model in the interval form and then solves this model by interval arithmetic. This method obtains accurate and robust estimates via a single random sampling of measurements and is computationally efficient. The comparative analysis in the IEEE 34-bus distribution system points to improved estimation results relative to the nonlinear WLS-based method.