scholarly journals Application and Evolution for Neural Network and Signal Processing in Large-Scale Systems

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Dongbao Jia ◽  
Cunhua Li ◽  
Qun Liu ◽  
Qin Yu ◽  
Xiangsheng Meng ◽  
...  
Keyword(s):  
Signal Processing ◽  
Large Scale ◽  
Brain Activity ◽  
Low Frequency ◽  
Frequency Characteristics ◽  
Brain Diseases ◽  
Time Dimension ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Low Frequency Power

Low frequency oscillation is an important attribute of human brain activity, and the amplitude of low frequency fluctuation (ALFF) is an effective method to reflect the characteristics of low frequency oscillation, which has been widely used in the treatment of brain diseases and other fields. However, due to the low accuracy of the current analysis methods for low frequency signal extraction of ALFF, we propose the Fourier-based synchrosqueezing transform (FSST), which is often used in the field of signal processing to extract the ALFF of the low frequency power spectrum of the whole-time dimension. The low frequency characteristics of the extracted signal are compared with those of FSST and fast Fourier transform (FFT) through the resting-state data. It is clear that the signal extracted by FSST has more low frequency characteristics, which is significantly different from FFT.

scholarly journals Low-Frequency Oscillation in Power System

2020 ◽  
Vol 9 (3S2) ◽  
pp. 5-9
Keyword(s):  
Signal Processing ◽  
Power System ◽  
Low Frequency ◽  
Measurement Unit ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Interconnected Power System ◽  
Oscillation Detection ◽  
Processing Techniques ◽  
Signal Processing Techniques

Low-frequency oscillation can collapse the stability of the power system, which is considered to be one of the most significant challenges to a power system engineer. In earlier decades modal analysis was carried out for identifying lowfrequency oscillation modes, which have various drawbacks. In the present era, with the application of the Phasor measurement unit & various signal processing techniques, identification of lowfrequency oscillation is being carried out with accuracy to an extent. This paper provides a survey of recent research and development in the field of identification of low-frequency oscillation by different signal processing techniques. It is expected that this literature survey will provide researchers with some future direction in finding relevant references and developing suitable techniques for low-frequency oscillation detection in the interconnected power system.

Survey of Ambient Excitation Based Power Oscillation Analysis Methods

2012 ◽  
Vol 614-615 ◽  
pp. 1013-1018
Author(s):  
Chang Liu ◽  
Chang Song Li ◽  
Hua Qiang Li
Keyword(s):  
Power System ◽  
Large Scale ◽  
Low Frequency ◽  
Fundamental Principle ◽  
Low Frequency Oscillation ◽  
Operation Analysis ◽  
Power Oscillation ◽  
Oscillation Analysis ◽  
Low Frequency Power ◽  
Ambient Excitation

In large-scale power system, low frequency power oscillation is becoming a serious threat to the power system operation. Analysis of low frequency oscillation includes model-based method and ambient-excitation-based method. Based on the investigation of the related recently-published papers, this paper presents a survey of ambient-excitation-based method. Firstly, the fundamental principle and underlying theory of ambient-excitation-based method are summarized. Furthermore, several ambient-excitation-based methods are categorized and their characteristics are introduced.

On the mechanism and control for the ultra-low frequency oscillation in NY Power Grid with large-scale hydropower

2019 ◽  
Vol 17 (3) ◽  
pp. 241-251
Author(s):  
Ancheng Xue ◽  
Jiawei Wang ◽  
Chao Zheng ◽  
Joe H. Chow ◽  
Tianshu Bi
Keyword(s):  
Large Scale ◽  
Power Grid ◽  
Low Frequency ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
And Control

Analysis and Control on Oscillation Characteristics of Smart Grid with Large-Scale Wind Power Integration

2013 ◽  
Vol 732-733 ◽  
pp. 1342-1347
Author(s):  
Jia Chen Zhong ◽  
Wen Ying Liu ◽  
Wei Zheng
Keyword(s):  
Wind Power ◽  
Large Scale ◽  
Damping Ratio ◽  
Low Frequency ◽  
Power Network ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Wind Power Integration ◽  
And Control ◽  
Oscillation Characteristics

To deal with the problem of large-scale wind power integration and its influence on low frequency oscillation characteristics of Gansu power network, this paper built the low frequency oscillation simulation model with large amount of wind power integration, and proposed an index, namely grid structural weakness degree, based on the damping ratio index, to investigate low frequency oscillation characteristics. The simulation shows that the damping ratio decreases as the wind turbine output increases; and when the damping ratio is lower than 3%, or weakness degree lower than 4, it is more likely to cause low frequency oscillation in Gansu power network, and early-warning should be taken. The analysis provides a reference for low frequency oscillation early-warning and control.

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