Artificial neural networks in high voltage transmission line problems

被引:8
|
作者
Ekonomou, L.
Kontargyri, V. T.
Kourtesi, St
Maris, T. I.
Stathopulos, I. A.
机构
[1] Hellen Publ Power Corp SA, Distribut Div, Athens 10432, Greece
[2] Natl Tech Univ Athens, Sch Elect & Comp Engn, High Voltage Lab, Athens 15780, Greece
[3] Technol Educ Inst Chalkida, Dept Elect Engn, Psachna Evias 33440, Greece
关键词
artificial neural networks; critical flashover voltage; high voltage transmission lines; polluted insulators;
D O I
10.1088/0957-0233/18/7/058
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
According to the literature high voltage transmission line problems are faced using conventional analytical methods, which include in most cases empirical and/or approximating equations. Artificial intelligence and more specifically artificial neural networks (ANN) are addressed in this work, in order to give accurate solutions to high voltage transmission line problems using in the calculations only actual field data. Two different case studies are studied, i.e., the estimation of critical flashover voltage on polluted insulators and the estimation of lightning performance of high voltage transmission lines. ANN models are developed and are tested on operating high voltage transmission lines and polluted insulators, producing very satisfactory results. These two ANN models can be used in electrical engineers' studies aiming at the more effective protection of high voltage equipment.
引用
收藏
页码:2239 / 2244
页数:6
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