Abstract

SUMMARY Measurement algorithm is the important element of Intelligent Electronic Devices (IEDs) used in protection and monitoring of transmission and distribution networks. The function of the measurement algorithm is to estimate fundamental frequency component (phasor) of current and voltage signals recorded during network faults. The estimated fundamental component is used by variety of protection algorithms for the successful operation of the IEDs. The most popular measurement algorithm is the Discrete Fourier Transform (DFT). However, the estimation of the fundamental frequency component by the DFT algorithm will produce error if input signal contains nuisance components such as a decaying DC offset. This paper evaluates the performance of DFT measurement algorithm when its input signal is influenced by variety of the nuisance components. Various random factors will impact the amount of nuisance components present in a measured signal. Therefore, we propose a novel global uncertainty and sensitivity analysis technique to determine in a systematic way the impact of nuisance components on the performance of measurement algorithms. In addition to the full-cycle DFT, we analyze performance of half-cycle DFT and full-cycle cosine filter algorithms. Impact of nuisance components due to current transformer (CT) saturation and without saturation was studied. Steady-state and transient performance indices are defined to evaluate the performance of the algorithms. Copyright © 2012 John Wiley & Sons, Ltd.

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