Research of Intelligent Substation Condition Monitoring Based on the Neural Network

Da Peng Chai; Qiang Qiang Xue; Ling Mei Wang; Xing Yong Zhao

doi:10.4028/www.scientific.net/AMM.325-326.692

Paper Titles

Simulation System Research on Live Working for 500kV Transmission Line
p.673

New-Type Hybrid Active Power Filter of Microgrid
p.677

A New Fault-Positions Method Based on Interpolation for the Area of Vulnerability to Voltage Sags
p.681

Application of Smart Phone in Distribution Network Inspection and Troubleshooting
p.687

Research of Intelligent Substation Condition Monitoring Based on the Neural Network
p.692

Research on a Coal Gangue Identification Device
p.699

Applications in Medical Reagent Test Equipment of Semiconductor Refrigeration
p.703

Optical Fiber Sensor Salt Dense On-Line Monitoring Research
p.708

Fast Interrogation Method Based on Two Superimposed Fiber Bragg Gratings
p.712

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 325-326Research of Intelligent Substation Condition...

Research of Intelligent Substation Condition Monitoring Based on the Neural Network

Abstract:

The substation electric power equipment condition monitoring is the basis of intelligent substation. This paper analyzes the composition of the substation electric power equipment condition monitoring system and monitoring parameters, and with the transformer condition monitoring as an example, this paper proposes fault diagnosis methods of electric power equipment using artificial neural network(ANN).

You might also be interested in these eBooks

Manufacturing Engineering and Process II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 325-326)

Pages:

692-696

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.325-326.692

Citation:

Cite this paper

Online since:

June 2013

Authors:

Da Peng Chai, Qiang Qiang Xue, Ling Mei Wang, Xing Yong Zhao

Keywords:

Artificial Neural Network (ANN), Condition Monitoring, Intelligent Sub-Station

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] FENG Jun. (2011). Intelligent Substation theory and test technology. Beijing:China Electric Power Press.

Google Scholar

[2] JIN Yi, LIU Wei, CHA xian-guang and FEI yi-jun.(2012)."The Technology of State Monitoring System and its Application in Smart Substation". Jiangsu Electrical Engineering. 31 (2):12-15.

Google Scholar

[3] LIU Ying-Mei, YANG Wan-Hui, ZHANG Jian, XU Min and KONG Bin. (2000). "Fault diagnosis system for substation based on ANN and its robustness". Relay. 28 (9):19-22.

Google Scholar

[4] LAN Guo-liang, GUAN Gen-zhi, ZHANG Lin, ZHANG Hai-long and WANG Yi. (2006). "Study on Insulation On-line Monitoring Expert System in substation Based on Neural network". High Voltage Apparatus. 42 (2):99-101.

Google Scholar

[5] State Grid Corporation. (2010). The key equipment (system) of the strong smart grid development planning. Beijing: State Grid Corporation.

Google Scholar

[6] State Grid Corporation. (2010). Smart grid technology standard system planning. Beijing: State Grid Corporation.

Google Scholar

[7] State Grid Corporation. (2009). Intelligent Substation Technical Guidelines. Beijing: State Grid Corporation.

Google Scholar

[8] WANG De-wen, WANG Yan and DI Jian.(2011). "Design Scheme of Condition Monitoring System for Smart Substation". Automation Of Electric Power Systems. 35 (18):51-56.

Google Scholar

[9] WU Ren-nian and ZENG Xiao-dong. (2011). "Transformer fault prediction based on BP neural network ". China Electric Power Education. (30):146-147.

Google Scholar