Wide and Deep Convolutional Neural Networks for Electricity-Theft Detection to Secure Smart Grids
Sun Yat-sen University · Macau University of Science and Technology
Abstract
Electricity theft is harmful to power grids. Integrating information flows with energy flows, smart grids can help to solve the problem of electricity theft owning to the availability of massive data generated from smart grids. The data analysis on the data of smart grids is helpful in detecting electricity theft because of the abnormal electricity consumption pattern of energy thieves. However, the existing methods have poor detection accuracy of electricity theft since most of them were conducted on one-dimensional (1-D) electricity consumption data and failed to capture the periodicity of electricity consumption. In this paper, we originally propose a novel electricity-theft detection method based on wide…
Citation impact
- FWCI
- 18.71
- Percentile
- 100%
- References
- 43
Authors
5Topics & keywords
- Electricity
- Computer science
- Convolutional neural network
- Smart grid
- Deep learning
- Component (thermodynamics)
- Consumption (sociology)
- Artificial intelligence
- Affordable and clean energy