scholarly journals Time-time matrix z-score vector-based fault analysis method for series-compensated transmission lines

2017 ◽  
Vol 25 ◽  
pp. 2647-2659 ◽  
Author(s):  
Oveis ASGARI GASHTEROODKHANI ◽  
Behrooz VAHIDI ◽  
Aydin ZABOLI
2021 ◽  
Author(s):  
J. Deng ◽  
S. Liang ◽  
L. Z. Zhu ◽  
L. Yao ◽  
F. Duan ◽  
...  

Author(s):  
Xuecen Zhang ◽  
Qiang Liu ◽  
Yi Tang ◽  
Guofeng Liu ◽  
Xin Ning ◽  
...  

2018 ◽  
Vol 101 (5) ◽  
pp. 3-11
Author(s):  
YUSUKE NOZAKI ◽  
YOSHIYA IKEZAKI ◽  
MASAYA YOSHIKAWA

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 319
Author(s):  
Hongchun Shu ◽  
Na An ◽  
Bo Yang ◽  
Yue Dai ◽  
Yu Guo

The probability of a single pole-to-ground fault in high voltage direct current (HVDC) transmission lines is relatively high. For the modular multilevel converter HVDC (MMC-HVDC) systems, when a single pole-to-ground fault occurs, the fault current is small, and it is difficult to identify the fault quickly. Through a detailed analysis of the characteristics of the single pole-to-ground fault of the MMC-HVDC transmission line, it is found that the single pole-to-ground fault has obvious capacitance-related characteristics, and the transient process after the single pole-to-ground fault is the discharge process of the distributed capacitance of the line. However, other faults do not have such obvious capacitance-related characteristics. Based on such feature, this paper proposes a novel capacitive fuzzy identification method to identify the single pole-to-ground fault. This algorithm can effectively identify both the fault of single pole-to-ground and the fault pole, which can contribute to the large database of the future smart grid.


Risks ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 94
Author(s):  
Mariña Martínez-Malvar ◽  
Laura Baselga-Pascual

Systemic Banking crises are a recurrent phenomenon that affects society, and there is a need for a better understanding of the risk factors to support prudential regulation and reduce unnecessary risk intake in the financial system. This paper examines the main bank risk determinants in Latin America. The period analysed covers the timespan from 1999 to 2013, including the systemic banking crisis episodes in Argentina (2001–2003) and Uruguay (2002–2005). We apply a new data-driven comparable methodology to classify and select commercial banks from the sample. We study bank risk proxied by the Z-score. We use the system-GMM estimator as our main empirical analysis method. According to our results, well capitalized, liquid, and traditional commercial banks are less risky. We perform robustness tests by applying OLS, and the results resemble our original model.


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