On waveform distortion in the frequency range of 2 kHz–150 kHz—Review and research challenges

For reasonable power quality assessment of transient disturbances in electric power systems, new transient power quality indices are developed based on a signal processing technique, time-frequency analysis. Based on the time-frequency distribution of a transient disturbance, a set of time-frequency based power quality indices are developed. In this paper, the instantaneous disturbance energy ratio, normalized instantaneous disturbance energy ratio, instantaneous frequency, and instantaneous K-factor are suggested for transient power quality assessment. Time-frequency based power quality indices allow one to quantify the effects of transient disturbances with high-resolution and accuracy.

Power quality indices for transient disturbances

The effective harmonics estimation for measuring power signals has become an important issue in the power quality assessment. By reviewing those commonly used Kalman filter-based models, some limitations for harmonics estimation can be observed. In this paper an extended real model of Kalman filter combined with a resetting mechanism for accurately tracking time-varying harmonic components of power signals is presented. The usefulness of the proposed algorithm is demonstrated by a simple laboratory setup with LabVIEW program and the dedicated hardware for harmonics monitoring. Results show that the proposed method can achieve more accurate and robust measurement of harmonic amplitudes and phase angles for the time-varying power signals among compared methods while the uncertainty testing performances required by IEC standard 61000-4-30 are satisfied.

Extended Real Model of Kalman Filter for Time-Varying Harmonics Estimation

Due to an increase of power-electronic equipment installation and other harmonic sources, the identification and estimation of harmonic loads are of concern in electric power transmission and distribution systems. Conventional harmonic state estimation requires a redundant number of expensive harmonic measurements. In this paper, we explore the use of a statistical signal-processing technique, known as independent component analysis (ICA) for harmonic source identification and estimation. If the harmonic currents are statistically independent, ICA is able to estimate the currents using a limited number of harmonic voltage measurements and without any knowledge of the system admittances or topology. The results are presented with computer simulations for the modified IEEE 30-bus test system.

Harmonic Load Identification Using Complex Independent Component Analysis

A critical and comprehensive review on power quality disturbance detection and classification

This paper represents Part I of a two-part article which summarizes the probabilistic aspects of harmonics in electric distribution systems. This first part reviews the problems associated with direct application of the fast Fourier transform to compute harmonic levels of nonsteady state distorted waveforms, and various ways to describe recorded data in statistical terms. Each statistical description is applied to a set of recorded data for illustration purposes.

Time-varying harmonics. I. Characterizing measured data

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Time-varying harmonics. I. Characterizing measured data