2020/02/13 by Vahid Sarfi, Amir Ghasemkhani, Sarfi, Vahid +7 · 1 citation
Engineering · #FOS: Electrical engineering #Fault Detection and Control Systems #Power System Optimization and Stability #Signal Processing (eess.SP) #Smart Grid Security and Resilience #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2002.07603
openalex publication_date 2020/02/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes a decentralized dynamic state estimation (DSE) algorithm with bimodal Gaussian mixture measurement noise. The decentralized DSE is formulated using the Ensemble Kalman Filter (EnKF) and then compared with the unscented Kalman filter (UKF). The performance of the proposed framework is verified using the WSCC 9-bus system simulated in the Real Time Digital Simulator (RTDS). The phasor measurement unit (PMU) measurements are streamed in real-time from the RTDS runtime environment to MATLAB for real-time visualization and estimation. To consider the data corruption scenario in the streaming process, a bi-modal distribution containing two normal distributions with different weights and variances are added to the measurements as the noise component. The performances of both UKF and EnKF are then compared for by calculating the mean-squared-errors (MSEs) between the actual and estimated states.