An Efficient Protection Scheme For Microgrid Based On Wavelet Transform And Data-Mining technique
UMA DEHARIYA, Dr. K.T.Chaturvedi, Vandana Sondhiya
Fault detection, microgrid protection, Feature extraction, Discrete wavelet transform, Data mining.
With the rising trend of the use of the potential of distributed energy resources, for the management of the ever-growing demand for electrical energy, the microgrid have come to the fore. Microgrid offers significant advantages in distribution systems but the integration of the synchronus DER and the renewable energy sources made the issue of protection. The failure related with the renewable energy sources is only 2-3 times higher than the rated voltage, as compared with a synchronous DER. For this reason, the associated security issues becoming even more complex. The value of the fault current depends on the mode of operation and the microgrid works on islanded and grid connected mode. Therefore, it is necessary to use an accurate and reliable technique that can operate in two modes with reliability and efficiently. In this context, an algorithm that is based on the structure of discrete wavelet transform (DWT) and bagged decision tree method is used in this. A direct current voltage signals are pre-processed with the DWT, and the standard deviation is calculated on the basis of the current participants in the course will be used to train the model based on data mining. The DWT-based feature extraction method we can use for all the useful features of the voltage and current signals in less estimated time.
Article Details
Unique Paper ID: 152654

Publication Volume & Issue: Volume 8, Issue 3

Page(s): 1065 - 1070
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