The Identification Algorithm of Power System’s Bad Data Based on Improved K-Means

Bao Yi Wang; Liang Zhu; Shao Min Zhang

doi:10.4028/www.scientific.net/AMM.713-715.958

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 713-715The Identification Algorithm of Power System’s Bad...

The Identification Algorithm of Power System’s Bad Data Based on Improved K-Means

Abstract:

The operation of power system generates a huge number of data. Manual screening of bad data is almost impossible to achieve. Bad data detection of the power system is the essential prerequisite for power system state estimation. So combined with the characteristics of bad data of the power system, this paper puts forwards an improved K-Means algorithm based on PSO. The traditional K-Means algorithm has disadvantage that it has low efficiency to determine the cluster’s center, but PSO algorithm has the ability to determine the cluster’s center quickly and accurately, this paper combines them together and take advantages of each of the two. The improved K-Means algorithm is based on PSO and verified the effectiveness of the algorithm. The results satisfy the requirements of screening bad data and reduce the false alarms and the probability of undetected and improve the recognition efficiency.

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Periodical:

Applied Mechanics and Materials (Volumes 713-715)

Pages:

958-961

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.713-715.958

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Online since:

January 2015

Authors:

Bao Yi Wang*, Liang Zhu, Shao Min Zhang

Keywords:

Detection of Bad Data, K-Means, Particle Swarm Optimization (PSO)

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