Voltage sag source identification method based on mutual approximation entropy
A voltage sag source and mutual approximate entropy technology, applied in the fault location and other directions, can solve the problems of difficult convergence and complex algorithms, and achieve the effect of avoiding difficult convergence, high identification efficiency, and high accuracy.
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[0063] Model parameters:
[0064] according to Figure 4 Voltage transient three-phase vector diagrams under various short-circuit fault conditions, using MATLAB and formulas to establish sample waveform data of 7 types of sags. In this method, the initial length of the window is m=2, and the similarity tolerance r=0.3.
[0065] Take 350 sets of actual voltage sag waveform data, and calculate the mutual approximation entropy between the actual waveform and the 7 types of sample waveforms in the sample library. The average mutual approximation entropy and the actual sag waveform are shown in Table 1. The mutual approximate entropy between the actual waveform and the sample waveforms of the sag type is the smallest, with an average value of about 0.3; the mutual approximate entropy between the actual waveform and sample waveforms of other sag types is large, with an average value between 0.6 and 1. This method is easy to classify when matching waveforms, and has good discrimin...
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