A Literature Survey on Techniques of Power Theft Detection

Abstract: Electricity companies lose much of their income, either through illegal connections or dishonesty of customers for personal gain. Investigators are deploying various systems to detect theft and reduce non-operational losses. Methods such as Support Vector Machine (SVM), Fuzzy C-means Clustering, Fuzzy logic, user profiling, genetic algorithm, etc. are used to detect electricity theft. There are two drawbacks to using these systems based on this methodology: the accuracy and the infrastructure required to run them, such as smart energy meters, etc. Using the current analysis of the system, a new system can be proposed which aims to improve the accuracy of theft detection

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