A GA-based grey prediction model for predicting the gas-in-oil concentrations in oil-filled transformer

被引：4

作者：

Wang, YY ^{[1
]}

Liao, RJ ^{[1
]}

Sun, CX ^{[1
]}

Du, L ^{[1
]}

Hu, HL ^{[1
]}

机构：

[1] Chongqing Univ, Minist Educ, Key Lab High Voltage Engn & Elect New Technol, Chongqing 400044, Peoples R China

来源：

CONFERENCE RECORD OF THE 2004 IEEE INTERNATIONAL SYMPOSIUM ON ELECTRICAL INSULATION | 2004年

关键词：

D O I：

10.1109/ELINSL.2004.1380456

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Dissolved-gas-analysis (DGA) techniques are widely used to diagnose oil-filled transformer insulation, but the conventional procedure acquiring the gas-in-oil concentrations is not timely. To make up the disadvantage, a new method based on a Genetic Algorithm and the Grey Theory to predict the gas-in-oil concentrations is proposed in this paper. The Grey Model (GM(1,1)) has been improved and a new optimized Grey Model (GM(1,1,beta)) has been constructed. The Genetic Algorithm has been applied to search the optimal parameters of the GM(1,1,beta) model. The validity of the GA-based GM(1,1,beta) model was verified with two prediction examples.

引用

页码：74 / 77

页数：4

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