Decentralized Dynamic State Estimation of Transmission Lines Using Local Measurements

Abstract

This paper presents a novel decentralized dynamic state estimation (DSE) method for estimating the dynamic states of a transmission line in real-time. The proposed method utilizes the sampled measurements from the local end of a transmission line, and thereafter DSE is performed by employing an unscented Kalman filter. The advantage of the proposed method is that the remote end state variables of a transmission line can be estimated using only the local end variables and, hence, the need for communication infrastructure is eliminated. Furthermore, an exact nonlinear model of the transmission line is utilized for estimation and the DSE of one transmission line is independent of the other lines. These in turn result in reduced complexity, higher accuracy, and easier implementation of the decentralized estimator. The proposed method is applied to a case study with realistic transmission line parameters. The results from the case study affirm that the proposed method accurately estimates the state variables under different operating conditions. Furthermore, robust performance is achieved with different noise variances and types. The proposed DSE method is envisioned to have potential applications in transmission line monitoring, control, and protection.

Keywords

• Dynamic state estimation
• Kalman filter
• power system monitoring
• transmission line
• unscented transformation