scholarly journals Feature selection for transient stability assessment based on kernelized fuzzy rough sets and memetic algorithm

Author(s):  
Xueping Gu ◽  
Yang Li ◽  
Jinghua Jia
2018 ◽  
Vol 318 ◽  
pp. 271-286 ◽  
Author(s):  
Yuwen Li ◽  
Yaojin Lin ◽  
Jinghua Liu ◽  
Wei Weng ◽  
Zhenkun Shi ◽  
...  

2013 ◽  
Vol 392 ◽  
pp. 544-547 ◽  
Author(s):  
Yang Li ◽  
Xue Ping Gu

This paper presents a new method for transient stability assessment (TSA) of power systems using kernel fuzzy rough sets and extreme learning machine (ELM). Considering the possible real-time information provided by phasor measurement units, a group of system-level classification features were firstly extracted from the power system operation condition to construct the original feature set. Then kernelized fuzzy rough sets were used to reduce the dimension of input space, and ELM was employed to build a TSA model. The effectiveness of the proposed method is validated by the simulation results on the New England 39-bus test system.


2020 ◽  
Vol 28 (5) ◽  
pp. 846-857 ◽  
Author(s):  
Linghe Kong ◽  
Wenhao Qu ◽  
Jiadi Yu ◽  
Hua Zuo ◽  
Guihai Chen ◽  
...  

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