LSTM and Bat-Based RUSBoost Approach for Electricity Theft Detection

Entropy - based electricity theft detection in AMI network

Advanced metering infrastructure (AMI), one of the prime components of the smart grid, has many benefits like demand response and load management. Electricity theft, a key concern in AMI security since smart meters used in AMI are vulnerable to cyber attacks, causes millions of dollar in financial losses to utilities every year. In light of this problem, the authors propose an entropy-based ele...

Electricity Theft Detection using Machine Learning

Non-technical losses (NTL) in electric power grids arise through electricity theft, broken electric meters or billing errors. They can harm the power supplier as well as the whole economy of a country through losses of up to 40% of the total power distribution. For NTL detection, researchers use artificial intelligence to analyse data. This work is about improving the extraction of more meaning...

Electricity and Gas Theft

Electricity Theft Detection Techniques for Distribution System in GUVNL

Electricity consumer dishonesty is a problem faced by all power utilities. Finding efficient measurements for detecting fraudulent electricity consumption has been an active research area in recent years. This paper presents a new approach towards Distribution Power Loss analysis for electric utilities using a novel intelligencebased techniques like Extreme Learning Machine (ELM), OS-ELM & Supp...

Electricity theft: a comparative analysis

Electricity theft can be in the form of fraud (meter tampering), stealing (illegal connections), billing irregularities, and unpaid bills. Estimates of the extent of electricity theft in a sample of 102 countries for 1980 and 2000 are undertaken. The evidence shows that theft is increasing in most regions of the world. The financial impacts of theft are reduced income from the sale of electrici...