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Multiple bad data identification in power system state estimation using particle swarm optimization

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2 Author(s)
Khwanram, J. ; Dept. of Electr. Eng., Kasetsart Univ., Bangkok, Thailand ; Damrongkulkamjorn, P.

This paper presents the approach of multiple bad data identification using particle swarm optimization (PSO). The identification problem is formulated as minimizing the number of bad data while maintaining the system observability and satisfying the chi2-test. The problem is considered as a combinatorial problem which could be solved by discrete binary PSO. The proposed method is tested on the IEEE 14-bus and IEEE 30-bus systems, where it could successfully identify multiple bad data with interacting and conforming errors. The proposed algorithm is also applied to an actual network of MEA, Thailand.

Published in:

Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2009. ECTI-CON 2009. 6th International Conference on  (Volume:01 )

Date of Conference:

6-9 May 2009

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