Development of power transformer thermal models for oil temperature prediction

被引：0

作者：

Tang, WH ^{[1
]}

Zeng, H

Nuttall, KI

Richardson, Z

Simonson, E

Wu, QH

机构：

[1] Univ Liverpool, Dept Elect Engn & Elect, Liverpool L69 3GJ, Merseyside, England

[2] Elect Power Res Inst, Beijing 100085, Peoples R China

来源：

REAL-WORLD APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS | 2000年 / 1803卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes a new thermal model of oil-immersed, forced-air cooled power transformers and a methodology for model construction using intelligent learning applied to on-site measurements. The model delivers the value of bottom-oil and top-oil temperatures for thermal performance prediction and on-line monitoring of power transformers. The results obtained using the new thermal model are compared with the results of a traditional thermal model and the results derived from artificial neural networks.

引用

页码：195 / 204

页数：10

共 50 条

[31] On the Development of Power Transformer Failure Models: an Australian Case Study
Martin, D.
Marks, J.
Saha, T.
Krause, O.
Russell, G.
Alibegovic-Memisevic, A.
2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2017,
[32] Multi-physics Analysis for Temperature Rise Prediction of Power Transformer
Ahn, Hyun-Mo
Kim, Joong-Kyoung
Oh, Yeon-Ho
Song, Ki-Dong
Hahn, Sung-Chin
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2014, 9 (01) : 114 - 120
[33] LSTM Networks for the Trend Prediction of Gases Dissolved in Power Transformer Insulation Oil
Dai, Jiejie
Song, Hui
Sheng, Gehao
Jiang, Xiuchen
2018 12TH INTERNATIONAL CONFERENCE ON THE PROPERTIES AND APPLICATIONS OF DIELECTRIC MATERIALS (ICPADM 2018), 2018, : 666 - 669
[34] Prediction of Dissolved Gas in Power Transformer Oil Based on Random Forests Algorithm
Deng, Ke
Xiong, Weihong
Zhu, Liming
Zhang, Hongzhi
Li, Zhengtian
2015 5TH INTERNATIONAL CONFERENCE ON ELECTRIC UTILITY DEREGULATION AND RESTRUCTURING AND POWER TECHNOLOGIES (DRPT 2015), 2015, : 1531 - 1534
[35] GRU-AGCN model for the content prediction of gases in power transformer oil
Luo, Diansheng
Chen, Wengang
Fang, Jie
Liu, Jianguo
Yang, Jinbiao
Zhang, Ke
FRONTIERS IN ENERGY RESEARCH, 2023, 11
[36] Prediction of the dissolved gas concentration in power transformer oil based on SARIMA model
Liu, Jiaxin
Zhao, Zijian
Zhong, Yuanchen
Zhao, Chenchen
Zhang, Guogang
ENERGY REPORTS, 2022, 8 : 1360 - 1367
[37] Prediction of Transformer Oil Temperature Based on an Improved PSO Neural Network Algorithm
Zhang, Zhiyan
Kong, Weihan
Li, Linze
Zhao, Hongfei
Xin, Chunwen
RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING, 2024, 17 (01) : 29 - 37
[38] A Top-oil Temperature Prediction Method for the Split Transformer Based on PSOGSA
Xin Zi
Wei Bengang
Liang Yongliang
Xu Yanshun
Guo Ruochen
Lou Jie
2018 3RD ASIA CONFERENCE ON POWER AND ELECTRICAL ENGINEERING (ACPEE 2018), 2018, 366
[39] Prediction model of transformer top oil temperature based on data quality enhancement
Dong, Naxin
Zhang, Ruoyu
Li, Zong
Cao, Bin
REVIEW OF SCIENTIFIC INSTRUMENTS, 2023, 94 (07):
[40] Prediction of Transformer Oil Temperature Based on Feature Selection and Deep Neural Network
Chen, Yongxin
Shiping, E.
Du, Zhenan
Zhang, Kanjun
Zhang, Gaofeng
2024 IEEE 15TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE, ICSESS 2024, 2024, : 94 - 98

← 1 2 3 4 5 →