A Study on Residual Current Device Nuisance Tripping Due to Grounding Resistance Value

2020 ◽  
pp. 717-723
Author(s):  
Izzatul Liyana ◽  
Farhan Bin Hanaffi ◽  
Mohd Hendra Bin Hairi
Keyword(s):  
Residual Current ◽  
Grounding Resistance ◽  
Nuisance Tripping ◽  
Current Device ◽  
Resistance Value

scholarly journals Grounding System Cost Analysis Using Optimization Algorithms

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3484 ◽  
Author(s):  
Jau-Woei Perng ◽  
Yi-Chang Kuo ◽  
Shih-Pin Lu
Keyword(s):  
Human Body ◽  
Rbf Neural Network ◽  
Grounding System ◽  
Grounding Resistance ◽  
Grounding Grid ◽  
Engineering Costs ◽  
System Data ◽  
And Performance ◽  
Touch Voltage ◽  
Resistance Value

In this study, the concept of grounding systems is related to the voltage tolerance of the human body (human body voltage tolerance safety value). The maximum touch voltage target and grounding resistance values are calculated in order to compute the grounding resistance on the basis of system data. Typically, the grounding resistance value is inversely proportional to the laying depth of the grounding grid and the number of grounded copper rods. In other words, to improve the performance of the grounding system, either the layering depth of the grounding grid or the number of grounded copper rods should be increased, or both of them should be simultaneously increased. Better grounding resistance values result in increased engineering costs. There are numerous solutions for the grounding target value. Grounding systems are designed to find the combination of the layering depth of the grounding grid and the number of grounded copper rods by considering both cost and performance. In this study, we used a fuzzy algorithm on the genetic algorithm (GA), multi-objective particle swarm optimization (MOPSO) algorithm, Bees, IEEE Std. 80-2000, and Schwarz’s equation based on a power company’s substation grounding system data to optimize the grounding resistance performance and reduce system costs. The MOPSO algorithm returned optimal results. The radial basis function (RBF) neural network curve is obtained by the MOPSO algorithm with three variables (i.e., number of grounded copper rods, grounding resistance value, and grounding grid laying depth), and the simulation results of the electrical transient analysis program (ETAP) system are verified. This could be a future reference for substation designers and architects.

Calibration of Residual Current Device (RCD) Testers

NCSLI Measure ◽  
2018 ◽  
Vol 12 (4) ◽  
pp. 28-37
Author(s):  
Steven Yang ◽  
Y. C. Chau
Keyword(s):  
Residual Current ◽  
Current Device

Novel protection scheme for residual current device-based electric fault time detection and touch current identification

2017 ◽  
Vol 11 (10) ◽  
pp. 2478-2488 ◽  
Author(s):  
Xiaohui Han ◽  
Wanxing Sheng ◽  
Songhuai Du ◽  
Juan Su ◽  
Guangeng Liu
Keyword(s):  
Residual Current ◽  
Protection Scheme ◽  
Current Device

Development of method to improve efficiency of residual current device under 1000 V on excavators of mining enterprises

2016 ◽  
Vol 52 (2) ◽  
pp. 325-331 ◽  
Author(s):  
B. B. Utegulov ◽  
A. B. Utegulov ◽  
A. B. Uakhitova
Keyword(s):  
Residual Current ◽  
Improve Efficiency ◽  
Current Device
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