Electricity Theft Detection Techniques

Electricity Theft Detection Techniques is a research topic within Electrical and Electronic Engineering. Science Explorer counts 6k research works in it since 1953. 10.2% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the detection and prevention of electricity theft in smart grids, particularly through the use of advanced metering infrastructure, machine learning, deep learning, and anomaly detection techniques. The research explores methods such as support vector machines, decision trees, convolutional neural networks, and feature engineering to address non-technical losses and improve the security of electricity distribution systems.

• Smart Grids
• Electricity Theft
• Detection
• Advanced Metering Infrastructure
• Non-Technical Losses
• Machine Learning
• Deep Learning
• Feature Engineering
• Supervised Learning
• Anomaly Detection