[1]Han Jianpeng,Lu Gaifeng,Cao Wensi.Research of the Transient Disturbance Detection Technology of Power System Using Local Mean Decomposition Algorithm[J].Journal of Zhengzhou University (Engineering Science),2016,37(01):29-33,59.[doi:10.3969/j.issn.1671-6833.201509013]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
37
Number of periods:
2016 01
Page number:
29-33,59
Column:
Public date:
2016-02-28
- Title:
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Research of the Transient Disturbance Detection Technology of Power System Using Local Mean Decomposition Algorithm
- Author(s):
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Han Jianpeng; Lu Gaifeng; Cao Wensi
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School of Electric Power, North China University of Water Conservancy and Hydropower, Zhengzhou, Henan, 450045
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- Keywords:
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LMD algorithm; transient disturbance signal; end effect; smart substation; power quality detection; HHT
- CLC:
-
-
- DOI:
-
10.3969/j.issn.1671-6833.201509013
- Abstract:
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The transient disturbance signals of power system have characteristics of nonlinear, irregular and mutation. Thus the local mean decomposition ( LMD) algorithm is used for detecting disturbance signals to get higher measurement accuracy. And the typical power quality transient disturbance signals including voltage swell signal, voltage sag signal, voltage interruption signal, transient oscillation signal, transient pulses sig-nal, frequency fluctuation signal, harmonics and voltage swell signals as well as actual disturbance signals oc-curred in smart substation are analyzed with the LMD algorithm. The simulation results show that LMD algo-rithm is rather effective in measuring transient disturbance signals of power system and has higher precision and faster computing speed than Hilbert-Huang transform ( HHT) algorithm.