| The current power quality sampling is all based on t he traditional Nyquist sampling theorem, for large and complex power grid, massive sampling data has brought great burden to transmission and storage. Combined with the advantages of compressed sensing, the artical explores to introduce analog-to-information converter based on compressed sensing, into the sample of power quality.Compressed sensing requires the sampled signal is sparse itself or in some sparse transformation. The artical establishes the model of common power quality disturbances, and sparsity has been analyzed. Then, two kinds of typical analog-to-information converters are compared, and random demodulator is chosen to test and verify compressed sensing in power quality.According to the reconstruction model of random demodulator, compressed sensing in power quality is simulated. Sensitivity of random demodulator to hardware parameters deviation is analyzed, the results have universal reference value for the hardware design of random demodulator. Then, simple, complex and measured power quality signals are sampled, reconstruction results show that random demodulator can realize the compressed sensing of common power quality disturbances. Based on simulation, random demodulator device is designed, and an experimental platform is built to further research compressed sensing in power quality.In addition, the reconstruction of compressed sensing in power quality is analyzed from three aspects. Results shown that sampled data two-dimensional mapping, an appropriate sparse transform base can im prove the reconstruction, and the sparsity adaptive algorithm has shown a strong adaptability to the reconstruction of power quality.Different from previous studies, oriented hardware implementation, the artical researched compressed sensing in power quality from analog front-end to digital reconstruction, which has an important reference value to the practical application of compressed sensing in power quality. |
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