Title :
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
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;
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
DOI :
10.1109/APPEEC.2009.4918396
