Hybrid S-transform and Kalman filtering approach for detection and measurement of short duration disturbances in power networks

This paper presents a new approach in the detection, localization, and classification of short duration disturbances in the power networks using a phase-corrected wavelet transform known as S-transform (ST) and an extended Kalman filter (EKF). The ST has excellent time-frequency resolution characteristics and provides detection, localization, and visual patterns suitable for automatic recognition of power quality events. The EKF, on the other hand, provides automatic classification and measurements of the frequently occurring power frequency short duration disturbances on the power networks. Thus, by combining both the ST and EKF, it is possible to completely classify and measure the short duration power quality disturbances. The proposed technique is applied to both simulated and experimentally obtained short duration power network disturbances in the presence of additive noise, and the results reveal significant accuracy in completely characterizing the power quality events.

I. Introduction

IN THIS PAPER, we propose a novel digital signal processing technique for the detection, classification and measurement of frequently occurring short duration disturbances (SDD) in the power networks, which are usually contaminated with noise. The disturbance occurring in the electric supply network is a major issue in manufacturing industries and causes very expensive consequences. These disturbances are primarily due to the use of nonlinear loads, power electronics equipment, and unbalanced loads. A recent survey attributes that 92% of power quality disturbances are voltage sags [14]. It has been reported that an interruption in the electric network or 30% voltage sag or swell for a very short duration (three to four cycles) can reset programmable controllers (PLC) for the entire assembly line. Such disturbances should be detected and classified accurately so that control action can be initiated. The proposed paper is an attempt in this direction to improve power quality in distribution networks.