Power signal frequency fine-tuning method and system

Abstract

The invention relates to an electric power signal frequency fine-tuning method and system. An actual electric power signal comprises a fundamental wave component, a sub-frequency harmonic component and a subharmonic component, and the amplitude of the fundamental wave component is the largest, so if the problem of non-integer period cut-off of a fundamental wave signal is solved, the problem of spectrum leakage caused by the non-integer period cut-off is solved to a great extent, and the degree of accuracy of sine parameter calculation is improved. The fundamental wave frequency of a signal sequence is changed through several multiplication sequences that are obtained, and integer period cut-off of a fundamental wave signal can be realized theoretically, thereby greatly improving the degree of accuracy of sine parameter calculation.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a method and system for fine-tuning the frequency of power signals. Background technique [0002] The frequency measurement, phase measurement and amplitude measurement of the power system are all sinusoidal parameter measurements in essence. Fast Fourier transform algorithm (FFT) and discrete Fourier transform algorithm (DFT) are the basic mathematical methods for the calculation of sinusoidal parameters. In these algorithms, the spectrum leakage problem caused by the non-integer cycle truncation of the signal sampling process is the main internal cause of the algorithm error, and the spectrum leakage problem is objectively unavoidable. [0003] There are also some improved methods, such as adding window function algorithm, interpolation correction algorithm and other algorithms. Although these algorithms can reduce the influence of spectrum leakage problem, the experimen...

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Problems solved by technology

In these algorithms, the spectrum leakage problem caused by the non-integer period truncation of the signal sampling process is the main internal cause of the algorithm error, and the spectrum leakage problem is objectively unavoidable

[0003] There are also some improved methods, such as adding window function algorithm, using interpolation correction algorithm and other algorithms. Although these algorithms can reduce the influence of spectrum leakage problems, the experimental results show that these algorithms are not suitable for the calculation of high-accuracy sinusoidal parameters.

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