Electricity-theft detection with deep learning

Electricity theft detection is a major concern in modern power systems, and has drawn the attention of both academia and industry. However, this problem has not been fully solved because of its complex intrinsic patterns, which are beyond the capacity of human decisions. Machine learning methods have been proven to be effective in handling such complex problems. Based on an open electricity theft detection dataset, a deep learning-based solution, the Temporal Convolutional Network (TCN), was proposed in this study and compared with existing machine learning schemes to demonstrate its effectiveness. The influence of the model parameters was also investigated in numerical experiments. The proposed TCN model is effective in detecting electricity theft behaviour in real-world electricity markets.