DocumentCode :
1778829
Title :
Power Line Multipath Transmission Model Parameters Based on Hybrid Particle Swarm Optimization Algorithm
Author :
Zhang Xuhui ; Peng Zhixuan ; Mao Suying ; Wang Wenping
Author_Institution :
Higher Educ. Key Lab. for Meas. & Control Technol. & Instrumentations of Heilongjiang, Harbin Univ. of Sci. & Technol., Harbin, China
fYear :
2014
fDate :
18-20 Sept. 2014
Firstpage :
235
Lastpage :
239
Abstract :
On the basis of the existing power line multipath transmission model, as the 0.5~20MHz actual low carrier communication channel voltage measurement data for the sample, this article makes the use of the fish hybrid particle swarm algorithm to finish multi-parameter identification. It introduces the location, speed and fitness of the PSO into the AFSA, meanwhile dynamically changes the visual and step of the AFSA, which simplifies parameter determination and improves optimization accuracy. Test and simulation results show that using this hybrid algorithm identifies the power line channel model, which can overcome the dispersion of model parameters, improve the fitting accuracy and shorten the identification time.
Keywords :
carrier transmission on power lines; multipath channels; particle swarm optimisation; power cables; power system parameter estimation; AFSA; PSO; artificial fish swarm algorithm; carrier communication channel voltage measurement data; hybrid particle swarm optimization algorithm; power line channel model; power line multipath transmission model parameter identification; Attenuation measurement; Marine animals; Parameter estimation; Particle swarm optimization; Power measurement; Visualization; Voltage measurement; Artificial fish swarm algorithm (AFSA); Parameter identification; Power line multipath model; particle swarm optimization (PSO);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement, Computer, Communication and Control (IMCCC), 2014 Fourth International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4799-6574-8
Type :
conf
DOI :
10.1109/IMCCC.2014.56
Filename :
6995026
Link To Document :
بازگشت