Voltage quality monitoring and perturb automatic classification method based on analysis in time-domain

Abstract

Time-domain characteristic of voltage signal is analyzed due to the methods of voltage quality monitoring based on time-domain analysis and automatic classification method of disturbance; four characteristic quantities used for classifying disturbing signal of electric power quality are extracted; an automatic classification method for disturbance of electric power quality is given out based on the four characteristic quantities. The method can conclusively and automatically identify the disturbing signals of electric power, such as a harmonic wave, an inter-harmonic wave, a wave and flickering, under voltage, overvoltage, oscillation transient voltage, voltage swell and sag, momentary interruption, and the like, and mixing disturbing signals from voltage signals. The generation time can be identified and strength of the disturbing signals can be evaluated. The method is little in calculated amount, which can be realized with single chip DSP, thus especially being applicable to on-line monitoring of voltage quality. Disturbing signal of various electric power qualities and the mixing disturbing signals can be automatically identified from a plurality of recorder data of substation busbar voltage, the generation time can be identified and the strength of the disturbing signals can be evaluated.

Description

technical field [0001] The invention relates to an automatic monitoring method for the voltage quality of a grid busbar, which is suitable for automatic monitoring of the busbar voltage quality of various substations and terminal power users. The utility model belongs to the technical field of electric power automation. Background technique [0002] In the modern power system, the application of power electronic equipment is more and more extensive, and various non-linear, impact and fluctuating loads are also greatly increased, so that the power quality pollution suffered by the power system is also becoming more and more serious. At the same time, sensitive electronic equipment puts forward higher requirements for power quality. As a commodity, electric energy is put into the market competition. Like other commodities, it will be priced on the Internet, and it will gradually be priced according to quality, high quality and high price. A scientific and reasonable assessme...

AI Technical Summary

Problems solved by technology

Time-frequency domain transform tools such as Fourier transform, wavelet transform, HHT transform, and S transform all have their own advantages in extracting the characteristics of power quality disturbance signals. However, when using a single transform tool to study the classification of power quality disturbances, there are still three common problems: Defects: First, it is difficult for a single transformation tool to extract all the characteristics of power quality disturbance signals, so the classification of disturbances is local; second, the proposed feature quantities for judging various disturbances lack clear physical meaning, which makes the classification of disturbances difficult. The further accurate estimation of various disturbances brings difficulties; the third is that the characteristic quantity of a certain disturbance will change its value due to the existence of another disturbance. Therefore, when encountering compound disturbances, the difficulty of classification and judgment will increase

Moreover, the above time-frequency domain transformation has a large amount of calculation, and it is difficult to classify the voltage disturbance signal online, and it is not suitable for the development of an online automatic monitoring and classification device for voltage disturbance signals using a single-chip microcomputer (DSP).

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