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Prof. Samy Mohamed Ghania :: Publications: |
Title: | STATISTICAL ANALYSIS OF SWITCHING OVERVOLTAGES AND INSULATION COORDINATION FOR A 500 kV TRANSMISSION LINE |
Authors: | A.H. Hamza , Samy M. Ghania , Ahmed M.Emam and Ahmed S. Shafy |
Year: | 2015 |
Keywords: | Not Available |
Journal: | The 19th International Symposium on High Voltage Engineering, Pilsen, Czech Republic, August, 23 – 28, 2015 |
Volume: | The 19th International Symposium on High Voltage Engineering, Pilsen, Czech Republic, August, 23 – 28, 2015 |
Issue: | The 19th International Symposium on High Voltage Engineering, Pilsen, Czech Republic, August, 23 – 28, 2015 |
Pages: | The 19th International Symposium on High Voltage Engineering, Pilsen, Czech Republic, August, 23 – 28, 2015 |
Publisher: | The 19th International Symposium on High Voltage Engineering, Pilsen, Czech Republic, August, 23 – 28, 2015 |
Local/International: | International |
Paper Link: | Not Available |
Full paper | Samy Mohamed Ghania_528.pdf |
Supplementary materials | Not Available |
Abstract: |
The rapid increase in transmission voltages to fulfil higher demand of the transmitted powers yields to put the switching surges as the governing factor in the insulation design process for EHV and UHV systems. The modern methods of insulation coordination make use of probabilistic concepts and statistical procedures especially for very high voltage systems. In this paper, a sophisticated and accurate approach to calculate the switching surge flashover rate (SSFOR) using Adaptive Neuro Fuzzy Interface System (ANFIS) is developed. The variation of switching overvoltages distribution along the transmission line under different system conditions is investigated. The statistical distributions of energization overvoltages for a typical Egyptian 500kV double-line from High–Dam to Samalut are derived from the results of 100 energization cases with statistical (random) switching using alternate transient program (ATP). The statistical distributions and its key values, such as mean value, standard deviation and 2% statistical overvoltages values have been recorded. The effects of various parameters on the energization overvoltages distribution such as line length, source strength and the use of shunt reactors to control the switching surge overvoltages are considered. The developed ANFIS system estimated the SSFOR for different input parameters for both the switching overvoltages and the insulation strength distributions with high accuracy. |