Research on Fault Diagnosis of Power System Based on Adaptive Immune Genetic Algorithm

Xiao Quan Li; Jing Chen Wang; Run Ling Li; An Quan Sun

doi:10.4028/www.scientific.net/AMR.816-817.812

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 816-817Research on Fault Diagnosis of Power System Based...

Research on Fault Diagnosis of Power System Based on Adaptive Immune Genetic Algorithm

Abstract:

In this article, the fault problem of power system is investigated with an adaptive immune genetic algorithm (AIGA) for the complications of fault. By introducing new crossover rate and mutation rate, considering the general characteristics of population, vaccines are extracted with dynamic self-adaption approach, thus avoiding the disadvantage of standard genetic algorithm. On the other hand, with the idea of survival of the fittest, the antibody population with low fitness is replaced by parts of new antibody generated randomly, which allows the variety of population. A general power system is employed to show the efficiency of the new method.

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Periodical:

Advanced Materials Research (Volumes 816-817)

Pages:

812-816

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.816-817.812

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Online since:

September 2013

Authors:

Xiao Quan Li, Jing Chen Wang, Run Ling Li, An Quan Sun

Keywords:

AIGA, Fault Diagnosis, Power System, Target Function

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References

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