Decision Tree and SVM Based Data Analytics for Theft Detection in Smart Grid
Abstract
Electricity theft is a major concern for the utilities. With the advent of smart meters, the frequency of collecting household energy consumption data has increased, making it possible for advanced data analysis, which was not possible earlier. Nontechnical losses, particularly due to electrical theft, have been a major concern in power system industries for a long time. As there are other different classification techniques like decision tree based algorithm. It is capable to enough to precisely detect and locate real- time electricity theft at every level in power transmissio n distribution. This proposes a comprehensive top-down scheme based on decision tree (DT).The proposed scheme is based on the combination of DT for rigorous analysis of gathered electricity consumption data. To collect the datasets in internet of US based Home appliances for detecting power theft in smart grid. After collecting the datasets by using ID3 algorithm to make the decision tree for that datasets in mat lab.
Author
K.K. Nithya
Dr. P. Ganeshkumar
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