Online static security assessment for cascading failure using stacked De-noising Auto-encoder

Author(s):  
Rizwan ul Hassan ◽  
Runjia Sun ◽  
Yutian Liu
2013 ◽  
Vol 64 (1) ◽  
Author(s):  
I. S. Saeh ◽  
M. W. Mustafa

This paper proposes RBF-NN for classification and performance evaluation of static security assessment in deregulated power system. This study suggests an attribute selection and classification algorithms for static security evaluation (SSE) and its impact is proposed. For the base case, pure pool dispatch (with no bilateral transactions) and bilateral transaction comparisons are discussed on IEEE57- bus system. In this paper, a comprehensive comparison of AI classifiers to examine whether the power system is secured under steady-state operating conditions is presented. The proposed classifier is implemented on a 30 and 57 IEEE test system. To assess the actual overall performance regarding studying techniques, this research proposes performance evaluation schemes vis CCR, TPR and TNR and implemented on various IEEE test systems. The simulation results have shown the powerfulness of the proposed method as compare to another proposed AI classifiers. 


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