A simple direct method for fast transient stability assessment of large power systems

1988 ◽  
Vol 3 (2) ◽  
pp. 400-412 ◽  
Author(s):  
Y. Xue ◽  
T. Van Cutsem ◽  
M. Ribbens-Pavella
Keyword(s):  
Power Systems ◽  
Transient Stability ◽  
Direct Method ◽  
Stability Assessment ◽  
Large Power ◽  
Fast Transient

scholarly journals A Critical Review of Data-Driven Transient Stability Assessment of Power Systems: Principles, Prospects and Challenges

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7238
Author(s):  
Shitu Zhang ◽  
Zhixun Zhu ◽  
Yang Li
Keyword(s):  
Power Systems ◽  
Transient Stability ◽  
Direct Method ◽  
Data Driven ◽  
Future Research ◽  
Stable Operation ◽  
Stability Assessment ◽  
Renewable Power ◽  
Feature Extraction And Selection ◽  
Actual Operation

Transient stability assessment (TSA) has always been a fundamental means for ensuring the secure and stable operation of power systems. Due to the integration of new elements such as power electronics, electric vehicles and renewable power generations, dynamic characteristics of power systems are becoming more and more complex, which makes TSA an increasingly urgent task. Since traditional time-domain simulations and direct method cannot meet the actual operation requirements of power systems, data-driven TSA has attracted growing attention from both academia and industry. This paper makes a comprehensive review from the following four aspects: feature extraction and selection, model construction, online learning and rule extraction; and then, summarizes the challenges and prospects for future research; finally, draws the conclusions of this review. This review will be beneficial for relevant researchers to better understand the research status, key technologies, and existing challenges in the field.

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 A Multifeature Fusion Approach for Power System Transient Stability Assessment Using PMU Data

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Yang Li ◽  
Guoqing Li ◽  
Zhenhao Wang ◽  
Zijiao Han ◽  
Xue Bai
Keyword(s):  
Power Systems ◽  
Power System ◽  
Transient Stability ◽  
Area Measurement ◽  
Feature Subset ◽  
Stability Assessment ◽  
Wide Area Measurement System ◽  
Feature Spaces ◽  
Proposed Model ◽  
Fusion Approach

Taking full advantage of synchrophasors provided by GPS-based wide-area measurement system (WAMS), a novel VBpMKL-based transient stability assessment (TSA) method through multifeature fusion is proposed in this paper. First, a group of classification features reflecting the transient stability characteristics of power systems are extracted from synchrophasors, and according to the different stages of the disturbance process they are broken into three nonoverlapped subsets; then a VBpMKL-based TSA model is built using multifeature fusion through combining feature spaces corresponding to each feature subset; and finally application of the proposed model to the IEEE 39-bus system and a real-world power system is demonstrated. The novelty of the proposed approach is that it improves the classification accuracy and reliability of TSA using multifeature fusion with synchrophasors. The application results on the test systems verify the effectiveness of the proposal.

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