Improving distance relay performance for heavily distorted voltage and current by accurate signal reconstruction using extended Kalman filter

Abstract

Distance relay plays a pivotal role in the detection of faults and subsequent isolation in transmission lines. However, severe distortion in the measured voltage and current waveforms (such as due to Current Transformer (CT) saturation), affects their performance. This paper focuses on a compensation method for signal reconstruction using Extended Kalman Filter (EKF) algorithm to improve relay functioning, enhancing the safety of transmission lines. The proposed fault detection scheme was tested extensively by running simulations using PSCAD and MATLAB for different types of faults at various distances and CT burden. The CT model in PSCAD was developed based on the Jiles-Atherton phenomenological theory in order to closely resemble a real-time CT with its saturation effects. The simulation results show that the proposed method is highly efficient in determining the exact fault point with improved zone approaching times even with measured signals having high noise and harmonic content. In cases where the conventional relay fails to detect the fault in the correct zone, the compensated data from the proposed method accurately detects the zone. Hardware experimental tests were carried out to further verify the effectiveness of the scheme in real-time, where the EKF based algorithm was implemented using a DSP-based microcontroller

Adhesion Coefficient Identification of Wheeled Mobile Robot under Unstructured Pavement

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