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New Application of Symbolic Regression Method Based on Genetic Programming in Power Quality Analysis

  • 2013-09-22
  • 815.7KB
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Harmonic analysis is an important issue in power quality analysis. Fourier transform and wavelet transform each have their limitations. This paper proposes a new method for power analysis using a symbolic regression method based on genetic programming. The article proposes a new method by analyzing traditional research methods. The feasibility of this method is demonstrated by combining a specific example. A full-bridge inverter simulation experiment is designed to generate analysis data. The Eurqa software is used to perform genetic selection calculations using a symbolic regression method to obtain the expressions of the sinusoidal component and the distortion component, thereby verifying the practicality of symbolic regression in power quality analysis. Compared with traditional methods, this method has less time information loss and clear functional relationships. It has wide applicability and good application potential in the field of power quality analysis.

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