Fault Identification Based on Nlpca in Complex Electrical Engineering

Yagang Zhang; Zengping Wang; Jinfang Zhang

doi:10.2478/v10187-012-0036-4

Abstract

The fault is inevitable in any complex systems engineering. Electric power system is essentially a typically nonlinear system. It is also one of the most complex artificial systems in this world. In our researches, based on the real-time measurements of phasor measurement unit, under the influence of white Gaussian noise (suppose the standard deviation is 0.01, and the mean error is 0), we used mainly nonlinear principal component analysis theory (NLPCA) to resolve fault identification problem in complex electrical engineering. The simulation results show that the fault in complex electrical engineering is usually corresponding to the variable with the maximum absolute value coefficient in the first principal component. These researches will have significant theoretical value and engineering practical significance.

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Fault Identification Based on Nlpca in Complex Electrical Engineering

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