DocumentCode :
3423461
Title :
Non-synchronous signal monitoring based on simulated annealing neural network
Author :
Li, Tianzan ; Wang, Xiaohua
Author_Institution :
Dept. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
fYear :
2009
fDate :
17-19 Aug. 2009
Firstpage :
358
Lastpage :
361
Abstract :
A neural network method combined with simulated annealing algorithm is proposed for power system harmonic analysis. This method is aimed at the system in which the sampling frequency cannot be locked on the actual fundamental frequency. By updating the relevant parameters including the learning rate of fundamental frequency, fundamental frequency, harmonic phases and amplitudes, the accurate harmonic estimating results can be obtained. The simulating results show that the harmonic estimation accuracy by the proposed approach is relatively better than that by the conventional harmonic analysis methods in the asynchronous case.
Keywords :
neural nets; power engineering computing; power system harmonics; signal processing; simulated annealing; fundamental frequency; harmonic estimation accuracy; harmonic phases; nonsynchronous signal monitoring; power system harmonic analysis; sampling frequency; simulated annealing neural network; Algorithm design and analysis; Analytical models; Frequency estimation; Harmonic analysis; Monitoring; Neural networks; Power system harmonics; Power system simulation; Sampling methods; Simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2009, GRC '09. IEEE International Conference on
Conference_Location :
Nanchang
Print_ISBN :
978-1-4244-4830-2
Type :
conf
DOI :
10.1109/GRC.2009.5255097
Filename :
5255097
Link To Document :
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