Transient Stability Assessment of a Power System with a Static Synchronous Series Compensator

2007 ◽  
Author(s):  
P. Kumkratug ◽  
P. Laohachai
Keyword(s):  
Power System ◽  
Transient Stability ◽  
Stability Assessment ◽  
Static Synchronous Series Compensator

scholarly journals Power System Transient Stability Assessment Based on Snapshot Ensemble LSTM Network

2021 ◽  
Vol 13 (12) ◽  
pp. 6953
Author(s):  
Yixing Du ◽  
Zhijian Hu
Keyword(s):  
Power Systems ◽  
Power System ◽  
Transient Stability ◽  
Short Term Memory ◽  
Risk Function ◽  
Stability Margin ◽  
Risk Level ◽  
Stability Assessment ◽  
Lstm Network ◽  
Hierarchical Assessment

Data-driven methods using synchrophasor measurements have a broad application prospect in Transient Stability Assessment (TSA). Most previous studies only focused on predicting whether the power system is stable or not after disturbance, which lacked a quantitative analysis of the risk of transient stability. Therefore, this paper proposes a two-stage power system TSA method based on snapshot ensemble long short-term memory (LSTM) network. This method can efficiently build an ensemble model through a single training process, and employ the disturbed trajectory measurements as the inputs, which can realize rapid end-to-end TSA. In the first stage, dynamic hierarchical assessment is carried out through the classifier, so as to screen out credible samples step by step. In the second stage, the regressor is used to predict the transient stability margin of the credible stable samples and the undetermined samples, and combined with the built risk function to realize the risk quantification of transient angle stability. Furthermore, by modifying the loss function of the model, it effectively overcomes sample imbalance and overlapping. The simulation results show that the proposed method can not only accurately predict binary information representing transient stability status of samples, but also reasonably reflect the transient safety risk level of power systems, providing reliable reference for the subsequent control.

scholarly journals Representational learning approach for power system transient stability assessment based on convolutional neural network

2017 ◽  
Vol 2017 (13) ◽  
pp. 1847-1850 ◽  
Author(s):  
Bendong Tan ◽  
Jun Yang ◽  
Xueli Pan ◽  
Jun Li ◽  
Peiyuan Xie ◽  
...  
Keyword(s):  
Neural Network ◽  
Power System ◽  
Convolutional Neural Network ◽  
Transient Stability ◽  
Learning Approach ◽  
Stability Assessment

scholarly journals Multi-machine transient stability by using static synchronous series compensator

2020 ◽  
Vol 11 (3) ◽  
pp. 1249
Author(s):  
Nur Ashida Salim ◽  
Nur Diyana Shahirah Mohd Zain ◽  
Hasmaini Mohamad ◽  
Zuhaila Mat Yasin ◽  
Nur Fadilah Ab Aziz
Keyword(s):  
Power System ◽  
Transient Stability ◽  
Single Phase ◽  
Power Transmission ◽  
System Stability ◽  
Phase System ◽  
Proportional Integral ◽  
Before And After ◽  
In Series ◽  
Static Synchronous Series Compensator

<span lang="EN-US">Transient stability in power system is vital to be addressed due to large disturbances that could damage the system such as load changes and voltage increases. This paper presents a multi-machine transient stability using the Static Synchronous Series Compensator (SSSC). SSSC is a device that is connected in series with the power transmission line and produces controllable voltage which contribute to a better performance in the power system stability. As a result, this research has observed a comparison of the synchronization of a three-phase system during single-phase faults before and after installing the SSSC device. In addition, this research investigates the ability of three different types of controllers i.e. Proportional Integral (PI), Proportional Integral Derivation (PID), and Generic controllers to be added to the SSSC improve the transient stability as it cannot operate by itself. This is because the improvement is too small and not able to achieve the desired output. The task presented is to improve the synchronization of the system and time taken for the voltage to stabilize due to the fault. The simulation result shows that the SSSC with an additional controller can improve the stability of a multi-machine power system in a single phase fault.</span>

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