A priori transient stability indicator of islanded power systems using Extended Equal Area Criterion

Author(s):  
P. McNabb ◽  
J. Bialek
Author(s):  
Yong Sun ◽  
Jinpeng Ma ◽  
Jürgen Kurths ◽  
Meng Zhan

The classic equal-area criterion (EAC) is of key importance in power system analysis, and provides a powerful, pictorial and quantitative means of analysing transient stability (i.e. the system's ability to maintain stable operation when subjected to a large disturbance). Based on the traditional EAC, it is common sense in engineering that there is a critical cleaning time (CCT); namely, a power system is stable (unstable) if a fault is cleared before (after) this CCT. We regard this form of CCT as bipartite. In this paper, we revisit the EAC theory and, surprisingly, find different kinds of transient stability behaviour. Based on these analyses, we discover that the bipartite CCT is only one type among four major types, and, actually, the forms of CCT can be diversified. In particular, under some circumstances, a system may have no CCT or show a periodic CCT. Our theoretical analysis is verified by numerical simulations in a single-machine-infinite-bus system and also in multi-machine systems. Thus, our study provides a panoramic framework for diverse transient stability behaviour in power systems and also may have a significant impact on applications of multi-stability in various other systems, such as neuroscience, climatology or photonics.


2008 ◽  
Vol 128 (1) ◽  
pp. 101-109 ◽  
Author(s):  
Akira Takeuchi ◽  
Takashi Sato ◽  
Kouya Takafuji ◽  
Hideaki Nishiiri ◽  
Kotaro Takasaki ◽  
...  

2021 ◽  
Vol 13 (12) ◽  
pp. 6953
Author(s):  
Yixing Du ◽  
Zhijian Hu

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.


2001 ◽  
Vol 137 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Luonan Chen ◽  
Asako Ono ◽  
Yasuyuki Tada ◽  
Hiroshi Okamoto ◽  
Ryuya Tanabe

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