| With the progress of society, which lead to the arrival of the full electrification era,businesses and individuals electricity consumption increase year by year. Power supplyquality also face more stringent requirements at the same time. The problem of how toenhance and improve power quality is urgently to be solved, and the solution to this questiondepends on the power quality can be made relative to the current scientific evaluation.Existing assessment technology is mainly made by collecting monitoring signal to evaluatethe power quality. Monitoring signals are usually disturbed by outside factors and producenoise. Therefore, removing the noise in monitoring power quality signal is included in theaccurate assessment of power quality and is to be a prerequisite.The optimization problem for power quality signal de-noising effect was studied anddiscussed. Firstly, select db3wavelet function wavelet which is suitable for power qualitysignal white Gaussian noise removal. Threshold selection criteria. Discuss the conditions ofits application their advantages and disadvantages in conventional four threshold values.Finally decide to use the a unified threshold as the criteria. Propose optimization ideas for thewavelet thresholding method. After the study of comparing the principles, algorithms andapplication limitations of different de-noising methods, optimize the thresholding function,toimprove the de-noising effect. Propose optimization scheme, and deduce the effect offeasibility and optimality. Finally, use simulation software matlab to de-noising for threeunique characteristics in power quality signal, and compare the results directly andquantittively through simulation waveform, signal to noise ratio,RMSE and a variety of ways.Compare simulation with each other and considerate quantify data, it can be concluded thatwith wavelet threshold function weighted combination, power quality signal de-noising effectplays a significant role in the optimization and improvement. |
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