Genetic Algorithm Based Multi-Agent System Applied in Health State Estimation in HVDC

Author

Wang Zhong-yong ; Xu Ying-jing

Author_Institution

Dept. of Electr. Eng., Wuyi Univ., Wuyishan

fYear

2009

fDate

27-31 March 2009

Firstpage

1

Lastpage

4

Abstract

A health state estimation scheme for HVDC (high voltage direct current transmission) system is proposed based on the genetic algorithm multi-agent . In order to apply the algorithm to HVDC state detection, the special technical problems are studied. The measured data in HVDC system can not be used to filter for the effect of the random noise. In the system, the calculation of HVDC state are induced from the consensus filter by which the signal affected by the noise can be dealt with. The system was applied to the HVDC benchmark model on account of the real data. According to the simulation results, the design has high reliability and accuracy, and the health state estimation problem may be have a new method to solve.

Keywords

HVDC power transmission; fault diagnosis; genetic algorithms; multi-agent systems; power engineering computing; power system state estimation; power transmission faults; power transmission reliability; random noise; HVDC algorithm; fault diagnosis; genetic algorithm; health state estimation; high-voltage direct current transmission; multiagent system; power system reliability; random noise effect; Artificial intelligence; Control systems; Fault diagnosis; Genetic algorithms; HVDC transmission; Load flow analysis; Multiagent systems; Power system faults; Power system stability; State estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific

Conference_Location

Wuhan

Print_ISBN

978-1-4244-2486-3

Electronic_ISBN

978-1-4244-2487-0

Type

conf

DOI

10.1109/APPEEC.2009.4918396

Filename

4918396