A novel approach to smart grid technology for electrical power transmission lines by a self-organized optical network node based on optical bistability

2011 ◽  
Author(s):  
Soichiro Nakanishi ◽  
Wakao Sasaki
Keyword(s):  
Transmission Lines ◽  
Optical Bistability ◽  
Power Transmission ◽  
Optical Network ◽  
Electrical Power ◽  
Network Node ◽  
Power Transmission Lines ◽  
Self Organized ◽  
Novel Approach ◽  
Smart Grid Technology

scholarly journals Analysis of Lightning Performance on 345 kV Transmission Lines Using Python Programming

2020 ◽  
Vol 3 (3) ◽  
pp. 65-76
Author(s):  
Fri Murdiya ◽  
Rofi Hariadi
Keyword(s):  
Transmission Lines ◽  
Power Transmission ◽  
Electrical Power ◽  
Object Oriented Programming ◽  
Computer Application ◽  
Lightning Strike ◽  
Percentage Error ◽  
Power Transmission Lines ◽  
Shielding Failure ◽  
Python Programming

One of main causes of interruption of electrical power supply is the lightning strike on overhead power transmission lines. The lightning performance of transmission line can be determined by value of shielding failure flashover rate (SFFOR) and back flashover rate (BFOR). The object of this study is to create a computer application to compute lightning performance on the transmission lines using Python programming. Pythons package tkinter used for program interface window. Application programming is done by using the concept of object-oriented programming (OOP) using Pythons keyword class. Validation shows that the application has applied the method correctly with a percentage error 0 % for SFFOR and 3.14 % for BFOR. The application can do analysis on the factors that affecting SFFOR and BFOR such as the effect of thunder day, tower foot resistance, and number of isolator disk. The results obtained in this study is computer application that can perform lightning performance analysis and analysis of factors that can affect it, such as thunder day, tower foot resistance and the number of isolator disk.

scholarly journals Corona Loss Minimization on High Voltage Transmission Line Network using Bundled Conductors.

2020 ◽  
Vol 9 (3) ◽  
pp. 887-891
Keyword(s):  
Transmission Line ◽  
Transmission Lines ◽  
Power Transmission ◽  
Hessian Matrix ◽  
Electrical Power ◽  
Power Transmission Lines ◽  
Long Distance ◽  
Power Stations ◽  
Line Network ◽  
Corona Losses

Electrical power generated and transmitted at a long distance away from the power stations is usually affected by inherent transmission line losses. The Ohmic and Corona losses which are predominantly common in power transmission lines are considered in this paper. These two losses are mathematically modeled with and without embedded bundled conductors. The resultant model which is a non-linear multivariable unconstrained optimized equation is minimized using the Hessian matrix determinant method for stability test purposes. The results obtained show that corona losses are minimized with embedded bundled conductors at a very low current value with large spacing distance between the bundled conductors. The decrease in the corona loss which is a consequence of spacing adjustment of the 2, 3, and 4 strands of bundled conductors was plotted using MATLAB 7.14. The plots obtained are in conformity with the inverse relation between corona loss and conductor spacing.

A Novel Approach to Utilize PLC to Detect Corroded and Eroded Segments of Power Transmission Lines

2015 ◽  
Vol 30 (2) ◽  
pp. 746-754 ◽  
Author(s):  
R. Jalilzadeh Hamidi ◽  
Seyed Hossein Hosseinian ◽  
Seyed Hossein Hesamedin Sadeghi ◽  
Zhihua Qu
Keyword(s):  
Transmission Lines ◽  
Power Transmission ◽  
Power Transmission Lines ◽  
Novel Approach

scholarly journals Water table depth prediction based on Deep learning models in Electrical Power Transmission Lines area

2021 ◽  
Author(s):  
Shijun Wang ◽  
Chang Ping ◽  
Ning Wang ◽  
Jing Wen ◽  
Ke Zhang ◽  
...  
Keyword(s):  
Water Table ◽  
Transmission Lines ◽  
Power Transmission ◽  
Model Simulation ◽  
Electrical Power ◽  
Water Table Depth ◽  
Weather Data ◽  
Power Transmission Lines ◽  
Data Simulation ◽  
Daily Data

Background: Predicting water table depth in Electrical Power Transmission Lines area presents great importance and helps the decision makers do the safety analysis during the project. The present study predicts the water table depth with observed weather data and hydrologic data. Method: The study first compared the results of LSTM, GRU, LSTM-S2S, and FFNN models in daily data simulation. Moreover, two scenarios (S1 and S2) were set to identify the effect of the water component on water table depth simulation. In addition, in order to analyze how data time scale influences the model simulation results, the monthly scale data was simulated by LSTM, GRU, and LSTM-S2S models. Result: The result indicated that LSTM-S2S was the best model for predicting daily water table depth among the four models. By contrast, FFNN performed the worst. LSTM and GRU model performed equally well both in daily data and monthly data simulation. S1 performed better than S2 in the water table depth simulation. The average daily performance of R2 and NSE was both higher than that in the monthly results with LSTM, GRU, and LSTM-S2S models. Conclusion: As a result, the method in the present study can be used to simulate the water table depth in the future in Electrical Power Transmission Lines area.

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