Classification of Voltage Sag based on Elliptic Metric

Voltage sag is one of the most serious power quality problems at present. The classification and recognition of voltage sag is the premise and foundation of other voltage research work. In this paper, after adding gauss window with adjustable window width to S transform, four types of voltage sag classification and recognition are realized by using elliptical metric method. The experimental results show that the S transform of single fundamental frequency can accurately judge the amplitude of the sag under different indentation amplitudes. Even if there is relatively large noise interference, its judgment results can meet the requirements. The classification effect of voltage sag based on ellipse metric is better and the recognition rate can reach 99.75%. 1. Foreword Voltage sag is a very serious power quality problem at present, which is more harmful than harmonic, voltage fluctuation and flicker, three-phase imbalance and other steady state power quality problems. Voltage sag has caused serious harm to power grid, enterprise, factory distribution and power system, and has also caused direct or indirect losses to people's daily life, and more or less affected the overall benefit of national economy. Therefore, to improve and control voltage sag which meet the needs of economic and social development to the greatest extent is the key problem to be solved. In the field of voltage sag research, the classification and recognition of voltage sag is not only the inherent attribute of voltage sag events, but also the premise and foundation of other voltage research work. So, the classification and recognition of depression has a special significance, which must be paid attention to and implemented from now on. At present, DQ transform[1], Fourier transform[2], short time Fourier transform[3], wavelet transform[4,5] and S transform[6,7] are used in the analysis of voltage sag problem. In Luo’s paper[1], the method of dq transform was used to test each eigenvalue, and the real-time compensatory and instantaneous measurement was studied. It was found that its dynamic performance was good, and it was widely used in electric power regulation devices and suitable for real-time and non-real-time situations. Fourier transform is the most widely used method, because it has been put forward for a long time, and there is a relatively large analytical and research ability in the analysis of stable signals, and it has a large proportion in power analysis. But its disadvantage is that it can only analyze some normal stability signals which can satisfy the integrity and orthogonality because of its harsh conditions and poor local transient capability. Based on short time Fourier transform (STFT), the amplitude, duration, source location and classification of voltage sag are studied in reference. A single frequency point and an optimal gauss window width are used in the S-transform calculation. In this paper, the voltage sag analysis method based on the single fundamental frequency S transform is adopted. Four kinds of voltage sag phenomena are studied, and the voltage sag signal is extracted and analyzed. The classification of voltage sag is 2018 International Conference on Big Data and Artificial Intelligence (ICBDAI 2018) Copyright © (2018) Francis Academic Press, UK DOI: 10.25236/icbdai.2018. 020 125 realized by Mahalanobis metric. 2. Single Fundamental Frequency S-transform Single Fundamental Frequency S-transform (SFST) is derived on the basis of S transform. It is the inheritance and development of S transform. Its principle is basically the same as S transform. The difference is that it is only calculated for a single frequency point, and only for the fundamental frequency point is calculated by SFST. The operation time can be greatly reduced. When the voltage sag signal is classified and analyzed, some characteristic quantities of the disturbance signal need to be calculated quickly and accurately, and only the fundamental frequency vector can be calculated to get the desired results. There is no need to calculate the amplitude vectors of all frequency points. The single fundamental frequency S transform ) , ( 0 f S λ of signal ) (t x is shown in formula 1. dt e e f t x f S t f j f t 0 2 0 2 2 2 ) ( 0 0 2 | | ) ( ) , ( π λ