With a large number of nonlinear loads connected to the power grid, the signal of the power system is seriously distorted, and the reasonable and accurate measurement of electric energy under the condition of distorted signal has become an urgent problem in the field of electric energy measurement. In order to solve the problem that the power measurement accuracy of power grid pulse distortion signal is not high, an active power measurement method based on adaptive wavelet is proposed. Firstly, the characteristics of pulsed distorted current signal are analyzed, and its mathematical expression is established by signal modulation. Then, the adaptive wavelet basis function is constructed based on the method of signal decomposition to the next level subscale space maximization. Secondly, the distorted pulse signal is decomposed and reconstructed based on the constructed adaptive wavelet base. Finally, the reconstructed signal is used for active energy division measurement. Simulation results show that the proposed method is effective and advanced, and the measurement accuracy is increased by 1.46% compared with traditional wavelet transform.

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Pulse Distortion Signal Active Power Measurement Method Based on Adaptive Wavelet Bases

  • Qun Yan,
  • Le Chen,
  • Jiarui Cui,
  • Tao Zhang,
  • Bo Zhang,
  • Qing Li

摘要

With a large number of nonlinear loads connected to the power grid, the signal of the power system is seriously distorted, and the reasonable and accurate measurement of electric energy under the condition of distorted signal has become an urgent problem in the field of electric energy measurement. In order to solve the problem that the power measurement accuracy of power grid pulse distortion signal is not high, an active power measurement method based on adaptive wavelet is proposed. Firstly, the characteristics of pulsed distorted current signal are analyzed, and its mathematical expression is established by signal modulation. Then, the adaptive wavelet basis function is constructed based on the method of signal decomposition to the next level subscale space maximization. Secondly, the distorted pulse signal is decomposed and reconstructed based on the constructed adaptive wavelet base. Finally, the reconstructed signal is used for active energy division measurement. Simulation results show that the proposed method is effective and advanced, and the measurement accuracy is increased by 1.46% compared with traditional wavelet transform.