A Stacked Machine and Deep Learning-Based Approach for Analysing Electricity Theft in Smart Grids
نویسندگان
چکیده
The role of electricity theft detection (ETD) is critical to maintain cost-efficiency in smart grids. However, existing methods for can struggle handle large consumption datasets because missing values, data variance and nonlinear relationship problems, there a lack integrated infrastructure coordinating load analysis procedures. To help address these simple yet effective ETD model developed. Three modules are combined into the proposed model. first module deploys combination imputation, outlier handling, normalization class balancing algorithms, enhance time series characteristics generate better quality improved training learning by classifiers. different machine (ML) methods, which uncorrelated skillful on problem ways, employed as base Finally, recently developed deep approach, namely temporal convolutional network (TCN), used ensemble outputs ML algorithms classification accuracy. Experimental results confirm that framework yields highly-accurate, robust performance, comparison other well-established models thus be practical tool industrial applications.
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ژورنال
عنوان ژورنال: IEEE Transactions on Smart Grid
سال: 2022
ISSN: ['1949-3053', '1949-3061']
DOI: https://doi.org/10.1109/tsg.2021.3134018