scholarly journals Assessment of the risk of failure of high voltage substations due to environmental conditions and pollution on insulators

2015 ◽  
Vol 22 (13) ◽  
pp. 9749-9758 ◽  
Author(s):  
Rafael Castillo Sierra ◽  
Oscar Oviedo-Trespalacios ◽  
John E. Candelo ◽  
Jose D. Soto
Keyword(s):  
High Voltage ◽  
Environmental Conditions ◽  
Risk Of Failure

Experimental and Estimation of Flashover Voltage of Outdoor High Voltage Insulators with Silica Filler Based on Grey Wolf Optimizer

2019 ◽  
Vol 20 (4) ◽  
Author(s):  
Elham Hassan ◽  
Loai Nasrat ◽  
Salah Kamel
Keyword(s):  
High Voltage ◽  
Environmental Conditions ◽  
Grey Wolf Optimizer ◽  
Electrical Characteristics ◽  
Grey Wolf ◽  
Silica Filler ◽  
Optimal Value ◽  
Flashover Voltage ◽  
Silica Concentration ◽  
Composite Samples

Abstract Epoxy is used widely in high voltage outdoor insulator because of its light weight (this avoids the need to use heavy cranes for their handling and installation and this reduces cost), easy handling, easy blending with additives, and having hydrophobicity. This paper focuses on improving epoxy electrical characteristics (flashover voltage) for high voltage outdoor insulator by adding silica filler. Composite of epoxy with silica filler: silica is prepared with 0 %, 10 %, 20 %, 30 % and 40 % weight percentages concentration. The flashover voltage (FOV) is tested under various environmental conditions with different samples lengths. Grey wolf optimizer (GWO) is developed to predict the best optimal value of flashover voltage under various environmental conditions using laboratory measurements of flashover voltage. The obtained results from GWO are compared with experimental measured data. Results showed an improvement with silica concentration at different samples lengths in flashover voltage for composite samples over epoxy without any additions. A comparison between three different conditions showed higher flashover voltage for samples in dry condition than that of samples in (wet, salt wet) conditions.

Investigasi Kondisi Permukaan Isulator Tegangan Tinggi berbasis Machine Learning TensorFlow

2020 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Salama Manjang
Keyword(s):  
Machine Learning ◽  
High Voltage ◽  
Diagnostic Tool ◽  
Environmental Conditions ◽  
Essential Role ◽  
Surface Condition ◽  
Electrical Energy ◽  
Training Data ◽  
The Earth ◽  
Learning Machine

The insulator plays an essential role in preventing the flow of current from the phase conductor to the earth through supporting towers so that the insulation is a significant part of the electrical energy transmission system. Generally, high-voltage insulators are widely used as external plug insulators, for that the performance of insulators is influenced by environmental conditions that indirectly affect the surface condition of the insulators. In this study, a diagnostic tool used in the testing surface of the insulator, which can classify mechanically whether the insulator is good or damaged. The classification method uses TensorFlow Machine learning. Machine Learning is used as a brain in the isolation classification process while TensorFlow functions to store training data and test data in the classification process. The results obtained from this study show the accuracy of classification data is 98%.

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