Estimating the electromechanical oscillation characteristics of power system based on measured ambient data utilizing stochastic subspace method

2011 ◽  
Author(s):  
Ni Jingmin ◽  
Shen Chen ◽  
Liu Feng
Keyword(s):  
Power System ◽  
Subspace Method ◽  
Ambient Data ◽  
Electromechanical Oscillation ◽  
Oscillation Characteristics

scholarly journals Research on the Unstable Branch Screening Method for Power System With High-Proportion Wind Power

2022 ◽  
Vol 9 ◽  
Author(s):  
Fei Tang ◽  
Xiaoqing Wei ◽  
Yuhan Guo ◽  
Junfeng Qi ◽  
Jiarui Xie ◽  
...  
Keyword(s):  
Power System ◽  
Wind Power ◽  
Wind Farm ◽  
Simulation Analysis ◽  
Screening Method ◽  
Prediction Method ◽  
Stability Margin ◽  
Screening Methods ◽  
Unstable Branch ◽  
Oscillation Characteristics

The sooner the system instability is predicted and the unstable branches are screened, the timelier emergency control can be implemented for a wind power system. In this paper, aiming at the problem that the existing unstable branch screening methods are lack prejudgment, an unstable branch screening method for power system with high-proportion wind power is proposed. Firstly, the equivalent external characteristics model of the wind farm was deduced. And based on this, the out-of-step oscillation characteristics of the power system with high proportion wind power was analyzed. Secondly, based on the oscillation characteristics, line weak-connection index (LWcI) was proposed to quantify the stability margin of a branch. Then an instability prediction method and an unstable branch screening method were proposed based on LWcI and voltage phase angle difference. Finally, the rapidity and effectiveness of the proposed method are verified through the simulation analysis of IEEE-118 system.

Mode identification method of low-frequency oscillation for power system based on ambient data

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hong-Yan Yan ◽  
Jin Kwon Hwang
Keyword(s):  
Power System ◽  
Curve Fitting ◽  
Low Frequency ◽  
Modal Identification ◽  
Measurement Unit ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Content Type ◽  
Identification Method ◽  
Ambient Data

Purpose The purpose of this paper is to improve the online monitoring level of low-frequency oscillation in the power system. A modal identification method of discrete Fourier transform (DFT) curve fitting based on ambient data is proposed in this study. Design/methodology/approach An autoregressive moving average mathematical model of ambient data was established, parameters of low-frequency oscillation were designed and parameters of low-frequency oscillation were estimated via DFT curve fitting. The variational modal decomposition method is used to filter direct current components in ambient data signals to improve the accuracy of identification. Simulation phasor measurement unit data and measured data of the power grid proved the correctness of this method. Findings Compared with the modified extended Yule-Walker method, the proposed approach demonstrates the advantages of fast calculation speed and high accuracy. Originality/value Modal identification method of low-frequency oscillation based on ambient data demonstrated high precision and short running time for small interference patterns. This study provides a new research idea for low-frequency oscillation analysis and early warning of power systems.

scholarly journals Closed-Loop Identification of Power System Based on Ambient Data

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Chao Wu ◽  
Chao Lu ◽  
Yingduo Han
Keyword(s):  
Power System ◽  
Closed Loop ◽  
Operating Conditions ◽  
Power Grids ◽  
Theoretical Research ◽  
Convergence Properties ◽  
Phasor Measurements ◽  
Closed Loop Identification ◽  
Ambient Data ◽  
Consistency Properties

Small fluctuations caused by random changes of loads exist continuously in power grids, which are called ambient signals. Using time-synchronized phasor measurements, the closed-loop identification of power system based on ambient data is discussed, which can reflect accurate operating conditions currently and provide critical information for system analyzing and controller designing. The closed-loop identification of a power system with multiple disturbances is theoretically studied, including the closed-loop identifiability, the consistency properties, and the convergence properties. The requirements for realizing the closed-loop identification are summarized, and the theoretical research results are validated by simulation examples.

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