Load Estimation of Power Transformers using an Artificial Neural Network

被引：0
|
作者：
Agudelo Zapata, Laura [1 ]
Velilla Hernandez, Esteban [2 ]
Lopez-Lezama, Jesus [2 ]
机构：
[1] Interconex Elect SA, Direcc Gest Operac, Medellin, Colombia
[2] Univ Antioquia, Dept Ingenieria Elect, Medellin, Colombia
来源：
2012 IEEE INTERNATIONAL SYMPOSIUM ON ALTERNATIVE ENERGIES AND ENERGY QUALITY (SIFAE) | 2012年
关键词：
Artificial Neural Networks; Electric Load Curve; Power Transformers and Prediction Time;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
This paper presents a methodology for load estimation of power transformers by means of an artificial neural network. To implement the proposed methodology the data of two power transformers, located in different places and with different operational conditions, were considered. Real data from a data base was provided by utility Interconexion Electrica S. A. (ISA). To forecast the load curves a neural network was trained using MATLAB, being able to fit a load curve with daily and weekly prediction times. The proposed method allows the estimation of load curve values in power transformers with an average percentage of relative error around 10%. The method described in this paper can be applied to other equipment with similar operating characteristics.
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页数：6
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